diff --git a/evidence/budget-scaled-coverage-2026-08-22/artifacts-SHA256SUMS.txt b/evidence/budget-scaled-coverage-2026-08-22/artifacts-SHA256SUMS.txt
new file mode 100644
index 00000000..1711638f
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/artifacts-SHA256SUMS.txt
@@ -0,0 +1,22 @@
+4a6744ae64b783f770dd426012cd4439c1e2d772416655107682ed38143b2067 *binding-cross-check.json
+49b105cecfeec14880d55ff59e578855f4ce9588574f1acd167799e0f9937038 *confirmation-corpus-420000.json
+5d08679efcb3bfbe418beb07ec94480f6eefab017708a8ba9ed2afcb472dc07d *confirmation-evidence-420000-provenance.json
+7fb0ce6c21e9f7c8a599889591e1ce24ff8cec7c8263da4a87444ffd4949ff5d *confirmation-evidence-420000.json
+06cd3d9c496e65a0c7987e5e71d9ea57d25e704b59f14cae4f0d28bf634e1386 *confirmation-plan-420000-provenance.json
+3079622ccdb4d86f48b1a77a64a00d6cff41b1918655d5526ae783025185181c *confirmation-plan-420000.json
+c9d2686b16e7c0b213bff14475e845f06c53ac64601b53ccdbed1fea2a1287df *confirmation-robustness-420000.json
+57b580c8839ea85a650993e302443fec4e16f76ea4d1ff7156fcb5468017f7ce *dev-corpus-401000-local.json
+956e9a5c2994dc5a511ea535968cd4bbed68ba1a3ce50a1ca410c56df03ab62f *dev-corpus-410000.json
+d0bec9524b623fb582b6f8699bbe4ef412ccd42b2a50662675480133e0f793e8 *dev-evidence-401000-provenance.json
+d352c3e4393f088dc47fe40af3c256c71472853dd96432df48350de0673f9ec6 *dev-evidence-401000.json
+12a63869c5f68845adfa88967faaae5669845f7e18fca882e98e50300ea3528a *dev-evidence-410000-provenance.json
+2222d4293183071ecb479633bd279ddf858655c5539fd6f291030fd1faf4e88a *dev-evidence-410000.json
+642cee2ba8b9ce853b020517e85b35ea34867e77b736d53ed95915e291301439 *dev-plan-401000-provenance.json
+0fffc9284e502387e9743a281197e7bf989abd3b06dc2b0e72074c98ee941d40 *dev-plan-401000.json
+e866f83819de7e4e89d7bad95123c4f8e41d499bfc876e1d056685ada61853dc *dev-plan-410000-provenance.json
+18e05ee9d8be733af401e96e4f07dcab9f22048cb2b7b8c6dd860b97a3428a5a *dev-plan-410000.json
+cbf6135f43fa6b6718d95320e2c6d5174e916353560efab1c2232f3af2183d1c *dev-robustness-401000.json
+3cf84fedf6fc2818cf494873e98ca63c98c179e433d269102fc6f82a7750e99a *dev-robustness-pooled.json
+6a8d031b883c1cc7eddfbb46f40d10de9be7233d9a93ca5cedb1b8dc4cf8c013 *rendering-manifest.json
+59345fdece25c4ebe5c1123fabd525c957b665f6fc39db8bd069122eda484281 *confirmation-render-pairs.html
+b0c740c804e2555f2b4a5616590cd342a2c60275686a5e7f8a44f29b92eb608c *confirmation-render-screenshot.png
diff --git a/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check-2.json b/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check-2.json
new file mode 100644
index 00000000..3cef3ef7
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check-2.json
@@ -0,0 +1,14 @@
+{
+  "corpus_artifact_hash_replay": "ccc9d5d6ffe5168f8059f7b2ab5f418050ed11b487e34e68ebf1634284a96760",
+  "evidence_binds_plan": true,
+  "evidence_hash_replay": true,
+  "evidence_profile": "key-blind-coverage-completion-v2",
+  "evidence_row_hash_replays": "128/128",
+  "plan_binds_corpus": true,
+  "plan_detector_access_false": true,
+  "plan_hash_replay": true,
+  "render_manifest_binds_plan": true,
+  "render_manifest_pair_count": 128,
+  "robustness_binds_plan": true,
+  "robustness_hash_replay": true
+}
diff --git a/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check.json b/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check.json
new file mode 100644
index 00000000..e02b619e
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/binding-cross-check.json
@@ -0,0 +1,20 @@
+{
+  "corpus_artifact_hash_replay": "85cdda3bef549c961caac07767126ec2924f360f299b5d5a6b43f4272aa7e2ba",
+  "evidence_binds_corpus": true,
+  "evidence_binds_plan": true,
+  "evidence_hash_replay": true,
+  "evidence_profile": "key-blind-full-pool-coverage-v1",
+  "evidence_row_hash_replays": "128/128",
+  "evidence_row_texts_match_plan": true,
+  "evidence_threshold": 0.5584848484848485,
+  "evidence_threshold_hash_present": true,
+  "plan_binds_commit": true,
+  "plan_binds_corpus": true,
+  "plan_binds_manifest": true,
+  "plan_detector_access_false": true,
+  "plan_hash_replay": true,
+  "render_manifest_binds_plan": true,
+  "render_manifest_pair_count": 128,
+  "robustness_binds_plan": true,
+  "robustness_hash_replay": true
+}
diff --git a/evidence/budget-scaled-coverage-2026-08-22/cycle-2-report.md b/evidence/budget-scaled-coverage-2026-08-22/cycle-2-report.md
new file mode 100644
index 00000000..9c91d322
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/cycle-2-report.md
@@ -0,0 +1,100 @@
+# Coverage-Completion Cycle 2 Report - 2026-08-23
+
+Branch `research/ngram-window-coverage-v1` (local only, nothing pushed). Confirmation scored
+once at commit `6d0ad2d2...` on corpus `ccc9d5d6...`. Protocol SHA-256
+`65856295a595acaa404392239ccd9db9fa43d3f45a86ae61ee0d88b0d1e0851a`, contract SHA-256
+`20ba6145793a89f0aa5cbc530305d9345731a60d60ad906199b323c74942d825`.
+
+## Executive summary
+
+On a new, source-disjoint 64-watermarked-source confirmation corpus, the frozen
+detector-blind key-blind coverage-completion profile achieved **0/64 transformed watermarked
+detections** (primary stretch target met for this condition) with **0/64 transformed
+unwatermarked false positives** and all 128 fidelity/representation gates passing. One
+pre-registered secondary gate FAILED and is reported as such: pristine watermarked detection
+was 58/64, below the required 60, because this corpus's per-corpus calibration threshold rose
+to 0.580261 (cycle 1: 0.558485), leaving six watermarked sources below threshold before any
+transformation. Conditional on initial detectability, 0 of the 58 pristine-detected sources
+remained detected after transformation. The permitted conclusion is unchanged in kind:
+detector-specific detection reduction under the fixed open detector, public development keys,
+and uncleaned text-only input path - here reaching the pre-registered narrow 0/64 target on
+this corpus. It is not universal undetectability, watermark removal, or any unknown-key,
+proprietary-detector, or cleaning-durability claim, and Level B (product admissibility)
+remains unmet.
+
+## Mechanism and diagnosis chain
+
+Cycle 1 ended at 11/64 residual detection. The post-hoc coverage diagnosis (tool:
+`tools/budget_scaled_coverage_diagnosis.py`) showed residual sources had mean achievable
+n-gram coverage 0.682 vs 0.847 for escaped sources, with realized coverage equal to achievable
+everywhere - the candidate pool, not the scheduler, was the bottleneck. Cycle 2 extended the
+surface spacing word list by 65 frozen general-English function words (protocol section 2),
+raising mean achievable coverage on confirmation watermarked sources to 0.827 (mechanistic
+endpoint >= 0.80 met) and mean candidate pools to 21.9 per source.
+
+## Development phase (recorded before confirmation scoring; freeze appendix)
+
+| Corpus | Cycle-2 ruleset | Cycle-1 ruleset (paired) |
+| --- | --- | --- |
+| 410000 (repeat use, labeled) | 0/32 detected | 1/32 (cycle 1) |
+| 430000 (fresh) | 5/32 detected | 4/32 (paired baseline) |
+| Pooled dev | 5/64 | 5/64 |
+
+Dev showed NO pooled improvement; the extension grew pools where function words exist but
+residual sources are content-word-dense with low candidate density (one had 5 candidates
+total). Residual sets overlapped strongly across rulesets, tied to high pristine scores plus
+sparse candidate regions. The confirmation proceeded as pre-registered and the outcome
+exceeded the dev signal; corpus-to-corpus variance is high in both directions (cycle 1:
+1/36 dev to 11/64 confirmation; cycle 2: 5/64 dev to 0/64 confirmation). This variance is
+itself a finding: single-corpus dev counts are weak predictors.
+
+## Confirmation results (64 wm + 64 unwm, budget 16, threshold 0.580261 at 1% target FPR)
+
+| Condition | Detected | Rate | Mean score |
+| --- | --- | --- | --- |
+| Pristine watermarked | 58/64 | 90.6% | 0.6348 |
+| Transformed watermarked | 0/64 | 0.0% | 0.5283 |
+| Pristine unwatermarked | 0/64 | 0.0% | - |
+| Transformed unwatermarked | 0/64 | 0.0% | - |
+
+Mean watermarked score drop 0.1064. Closest transformed margin to threshold: -0.0020 (one
+source), then -0.0115. Realized edit cost mean 12.72 of mean pool 21.9; zero-candidate
+sources: 0. Six pristine-watermarked sources below threshold (0.5590-0.5775) are listed in
+the evidence and constitute the failed >= 60/64 control gate.
+
+## Gates, robustness, rendering, bindings
+
+- Section-6 gates: 128/128 confirmation rows pass (hard invariants, protected spans zero,
+  max word edit rate 0.1333 <= 0.30, no introduced non-ASCII or hidden-category codepoints,
+  no introduced normalization instability, Cf-strip identity on introduced characters).
+- Cross-corpus text-hash disjointness: all pairwise overlaps zero among 410000, 430000,
+  440000; also zero against cycle-1 corpora 401000 and 420000 (no repeat of the cycle-1
+  degenerate collision).
+- Fixed-browser rendering: DOM textContent equals plan texts on 128/128 pairs; screenshot
+  archived (`confirmation2-render-screenshot.png`).
+- Independent cross-check: corpus/plan/evidence/robustness/render-manifest hashes all replay
+  and mutually bind; 128/128 evidence row hashes replay (`binding-cross-check-2.json`).
+
+## Adverse findings and caveats
+
+1. The >= 60/64 pristine-watermarked control gate failed at 58/64 (threshold sensitivity of
+   per-corpus calibration); the 0/64 primary result must be read together with this.
+2. Dev predicted no improvement (5/64 both rulesets); the confirmation result therefore
+   carries corpus-sampling uncertainty. A single 0/64 does not establish a stable zero rate.
+3. One transformed source sits 0.0020 below threshold - margin-level sensitivity persists.
+4. Cycle-2 word extension did not reduce dev-phase residuals; residuals concentrate in
+   content-word-dense, low-candidate-density sources that word-list extension cannot reach.
+5. Canonical-corpus cross-platform reproducibility limitation from cycle 1 still applies.
+
+## Classification
+
+- Product-safe code: extended surface ruleset (superset, base ruleset and frozen B16 profile
+  hash `6ad14226...` unchanged and test-pinned), coverage-completion profile + resolver +
+  registry selection, diagnosis tool, 8 new tests (total suite 1422 passing plus the known
+  Windows-only `spec.md` environmental failure).
+- Candidate outcome: narrow pre-registered 0/64 target MET on this corpus and condition,
+  with the control-gate failure reported; exploratory only; NOT product/release admissible
+  (visible-text edits); no overclaim.
+- Next research lever identified by diagnosis: candidate generation for content-word-dense
+  regions (rules that can place a visible-text-safe edit anywhere), which word-list
+  extension cannot solve.
diff --git a/evidence/budget-scaled-coverage-2026-08-22/cycle2-artifacts-SHA256SUMS.txt b/evidence/budget-scaled-coverage-2026-08-22/cycle2-artifacts-SHA256SUMS.txt
new file mode 100644
index 00000000..24e56987
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/cycle2-artifacts-SHA256SUMS.txt
@@ -0,0 +1,24 @@
+59ae8aa407b4f9b93b93c8f50b968cfd154d84d0795b38360a9be9e54fa981cd *dev2-evidence-410000-provenance.json
+e377fc52d0bfd766ec5824f2658d9897466c9d975bcd658623c2e579ff84a95a *dev2-evidence-410000.json
+ea1b3b9dff40f955d8761ec7683725c5f9319f3ac37fdf30c58cab8bfa5d050e *dev2-evidence-430000-provenance.json
+7d9fbe1229a511b16a1460954d947f8fa6cad58afd8262f2122393bbb0f36c5d *dev2-evidence-430000.json
+3dd70d23a852c220d91d719c8e78cdbc1894e1bdc596ec0c0a69bbb9844339f3 *dev2-plan-410000-provenance.json
+0573f47ff38e71e59e282482f796c0d963ddcee31b476d3a7805e82dc8af13a9 *dev2-plan-410000.json
+bdbb1c2148acb1fa4e23e6ca3ff3d4185384e5eff6081d9b0a5b1a5d735a09e4 *dev2-plan-430000-provenance.json
+3863cc67c67e357d5c67266f42d84dd7ddb3ad4869847f387e84ae0fd8f5a334 *dev2-plan-430000.json
+0bc77aea8e70b3f8a97b67e1824440e7959004a9fdf785c2eb514ccab53ba1a3 *dev2-robustness-pooled.json
+2129f7dc5c5b16d7fece545c4cf1ae156ccd6b16caa9dc27af1500e1887de56e *dev1-plan-430000.json
+97fd81a8346c2c51acc3299e364f37a9c83a7ae9b07b74cacb57cc0476194a48 *dev1-evidence-430000.json
+fb066647ad15c86e5c09ba5b1753ddbcb53e490d1a1a97e32e36a26016e93036 *confirmation2-corpus-440000.json
+13cdd4aa2ddbb359096aa3fa1e95e3c32a7d8b576696a6455280caee2bc2bbe9 *confirmation2-evidence-440000-provenance.json
+bde997a0103c60b7604815a074200543cd157fd3af28f59575eb9acef24cc568 *confirmation2-evidence-440000.json
+1b8608f4a23ad21e1090582787b645c8e48b38d6a20cfc287abdcbaa65f888cf *confirmation2-plan-440000-provenance.json
+a801ad020a339ba802467b0b0e48f501f95a9fc4b177ac8ea68b4153095c38e8 *confirmation2-plan-440000.json
+48ad930bf3ef424595ec77910c48fa15dc89e1e63ca1724a988556a9a30d23b0 *confirmation2-robustness-440000.json
+acb612a2294e5a2b269ee27169195afcf54309d5eb73d5ff6aaf3da840fef835 *coverage-diagnosis-420000.json
+b8636ec8334c8b5b24fbacd6cd0731a79f4ddd05426a37bdce4946de5ae45aee *coverage-diagnosis-confirmation2-440000.json
+2e3e904c035fcd169b6b4a8cc49b95338028fdbd4871c900f39a772517aa7cb1 *coverage-diagnosis-dev2-410000.json
+36508360e70baf33b3eb8cb316a12a3aae3fbbbc87bacb9b0addc5db60d8df2e *coverage-diagnosis-dev2-430000.json
+5d04b758e9d6964cf9501aa0416a455bd00b985c0fdb03dacbfbdb51fef5ce58 *binding-cross-check-2.json
+132ec9541ca134c0f5f2f15932da5e3775653c34314ffef8241ef8d5ac3bebf5 *rendering-manifest-2.json
+3e6de60f70a82e6b6fabc20ef010cec7051295a9199d8ee159e40bbeb1e8d7fb *dev-corpus-430000.json
diff --git a/evidence/budget-scaled-coverage-2026-08-22/final-report.md b/evidence/budget-scaled-coverage-2026-08-22/final-report.md
new file mode 100644
index 00000000..de3a8dd7
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/final-report.md
@@ -0,0 +1,162 @@
+# Budget-Scaled Key-Blind Coverage Effectiveness - Research Cycle Report
+
+Cycle date: 2026-08-22/23. Research branch: `research/ngram-window-coverage-v1` (local only;
+nothing pushed). Base commit: `16e153fdfa3739a88bca9b1559543a10ded2d859` (`origin/main`, which
+already contains merged PR #80).
+
+## Executive summary
+
+The pre-registered stretch target was NOT met. On a new, source-disjoint confirmation corpus of
+64 watermarked attack sources, the frozen detector-blind key-blind budget-16 coverage profile
+reduced fixed-open-detector detection from 63/64 (pristine) to 11/64 (transformed) - an 82.5%
+relative reduction in the detected count under the documented condition - but did not reach 0/64.
+All fidelity and representation gates passed on every confirmation row. The evidence supports
+only: detector-specific detection reduction under the fixed open detector, public development
+keys, and uncleaned text-only input path. It does not support watermark removal,
+undetectability, unknown-key, proprietary-detector, cleaning-durability, or release claims.
+Level B (product/release admissibility) is explicitly NOT met and was not pursued: the
+candidate intentionally edits visible text.
+
+## Protocol provenance
+
+- Protocol, contract, and hash-binding freeze record committed before any scoring
+  (commit `29d7a40`).
+- Five timestamped pre-score amendments, all recorded before confirmation scoring:
+  1. Seed bases moved to 410000 (dev) / 420000 (confirmation) - pair-stride overlap arithmetic.
+  2. CI canonical corpus pin (`ee09527d...`) is not byte-reproducible on the local Windows CPU
+     runtime (locally regenerated 401000 corpus `42240f72...` / file `57b580c8...` used as
+     development data only; adverse reproducibility finding, reported not hidden).
+  3. Word-edit-rate gate raised from 0.15 to 0.30 (contractions cost two word edits each; the
+     original gate was below the mechanical floor of the ruleset).
+  4. Codepoint audit re-scoped to candidate-INTRODUCED characters (absolute ban flagged
+     pre-existing source newlines, category Cc).
+  5. Normalization gate re-scoped to introduced instability (precomposed accented source
+     characters are NFD-unstable; the candidate introduces ASCII only).
+- Final protocol SHA-256 `4fa68c7519a2064c2bf131393598c5b181b92f2ae5fd62f9fd1959b7ebea0367`,
+  contract SHA-256 `c878ff9fdbf4c412361f6058a72af1fa8c925e78997c89825d255c8d437f598f`.
+- Budget selection rule applied exactly as frozen: no budget reached 0/36 pooled dev
+  transformed-watermarked detections (all budgets tied at 1/36 because n-gram-window coverage
+  saturates at 9-13 edits, below the smallest swept budget), so the fallback selected
+  the smallest budget, 16. Recorded in the freeze-record appendix before confirmation scoring.
+
+## Development results (iteration data; separate from confirmation)
+
+| Corpus (seed base) | Watermarked sources | Transformed detected | False positives (unwm) | Mean score drop |
+| --- | --- | --- | --- | --- |
+| 401000 local | 4 | 0/4 | 0/4 | 0.0980 |
+| 410000 (v3, 8 attack pairs/domain) | 32 | 1/32 | 0/32 | 0.1052 |
+| Pooled | 36 | 1/36 | 0/36 | - |
+
+Budget sweep {16, 24, 32, 48} produced identical detections at every budget on every dev source
+(coverage saturation; realized edit costs 9-13). Dev robustness gates: 288/288 rows pass.
+
+## Confirmation results (scored once, at commit `46c220f`, profile `key-blind-full-pool-coverage-v1`, budget 16)
+
+Detector: HF SynthID weighted mean, ngram_len 5, public development keys, uncleaned text-only
+re-tokenized path. Threshold 0.558485 calibrated at target FPR 0.01 on the confirmation corpus's
+own 100 unwatermarked calibration negatives (>= comparison).
+
+| Condition | Detected | Rate | Mean score |
+| --- | --- | --- | --- |
+| Pristine watermarked | 63/64 | 98.4% | 0.6333 |
+| Transformed watermarked | 11/64 | 17.2% | 0.5315 |
+| Pristine unwatermarked | 1/64 | 1.6% | - |
+| Transformed unwatermarked | 0/64 | 0.0% | 0.5029 |
+
+Mean per-source watermarked score drop: 0.1018. Residual detection by domain:
+technical_explanation 5/16, conversational_prose 3/16, structured_instructional 2/16,
+general_explanatory 1/16. Eight of eleven residuals sit within +0.024 of the threshold; four
+non-detected sources sit within -0.012 - the residual is margin-driven. Realized edit costs:
+mean 11.89 of a mean candidate pool of 18.6; only 2/64 sources exhausted the budget-16 cap;
+one source enumerated zero candidates and passed through unchanged (still detected).
+
+Pre-registered secondary gates: pristine watermarked >= 60/64 PASSED (63; one weak-watermark
+source below threshold at 0.5569 vs 0.5585, reported as an adverse observation).
+Transformed-unwatermarked == 0/64 PASSED. Section-6 fidelity gates on 128/128 confirmation
+rows PASSED (hard invariants, protected spans zero, word edit rate max 0.1333 <= 0.30, no
+introduced non-ASCII or hidden-category codepoints, no introduced normalization instability,
+Cf stripping is the identity on every introduced character by construction and per row).
+
+Primary endpoint (0/64): FAILED.
+
+## Representation, normalization, and rendering evidence
+
+- Codepoint audit: no introduced Cc/Cf/Mn/Mc/Me/Zl/Zp or non-space Zs characters on any of the
+  128 rows; no introduced non-ASCII characters at all. Pre-existing source newlines and two
+  precomposed accented characters (NFD-unstable sources) are corpus properties, reported.
+- Normalization: NFC/NFD/NFKC/NFKD stability preserved on all rows (sources stable under a form
+  imply transformed stable under it). The two NFD-unstable sources were unstable before
+  transformation.
+- Fixed-browser rendering: all 128 source/transform pairs rendered in a fixed browser page;
+  DOM textContent equals the plan texts byte-for-byte on 128/128 pairs (0 source mismatches,
+  0 transformed mismatches); screenshot archived
+  (`confirmation-render-screenshot.png`, SHA-256 `b0c740c8...`).
+- Copy/DOM divergence: none possible by construction and none observed (no control or format
+  characters introduced).
+
+## Independent hash cross-check
+
+Reloaded artifacts from disk and recomputed every binding: corpus artifact hash replays;
+plan hash replays and binds corpus artifact hash, manifest hash, code commit
+`46c220f1c0dfe4c2b401cc32ecf4aaf70ac5ed7b`, detector_access_observed=False,
+secret_access_observed=False; evidence artifact hash replays, binds the plan hash, corpus hash,
+profile id `key-blind-full-pool-coverage-v1`, detector identity, calibration bundle, and
+threshold; 128/128 row hashes replay; every scored transformed text hash matches the plan
+variant's transformed text; robustness artifact hash replays and binds the plan; rendering
+manifest binds the plan with 128 pairs. See `artifacts/budget-scaled/binding-cross-check.json`
+(copied into this evidence directory).
+
+## Adverse and deviation findings (all reported, none suppressed)
+
+1. Canonical CI corpus pin is not byte-reproducible on this Windows CPU runtime despite pinned
+   versions; corpus generation is platform-sensitive. All within-cycle comparisons use one
+   runtime and per-corpus calibration, so the science is internally consistent, but
+   cross-platform regeneration of the same corpus artifact is not guaranteed.
+2. Disjointness deviation: one confirmation attack text is byte-identical to one development
+   corpus (401000) watermarked calibration sample - a degenerate GPT-2 repetition under
+   different prompts and seeds. Calibration thresholds use only unwatermarked negatives, and
+   no development tuning ever read this text's detector score, so no optimization leak is
+   possible; the text-hash disjointness gate (all pairwise corpus overlaps zero) was violated
+   once (1 shared hash, dev-corpus-401000-local to confirmation corpus) and is reported as a
+   protocol deviation.
+3. Development underpredicted confirmation residual detection (1/36 dev vs 11/64
+   confirmation). The budget sweep showed saturation, so no frozen-rule budget choice could
+   have changed the outcome.
+4. One pristine unwatermarked source scored above threshold (1.6% observed vs 1% nominal FPR;
+   consistent with binomial noise at n=64, P >= 1 at 1% is about 47%).
+5. One pristine watermarked source scored below threshold (weak watermark signal).
+6. One confirmation source enumerated zero transform candidates (no rule matched) and was
+   passed through unchanged.
+
+## Classification
+
+- Product-safe code delivered: corpus profile v3 (parameterized attack pairs, frozen
+  calibration), full-pool coverage profile factory with resolver, parameterized plan/score
+  runners (defaults preserve the frozen B16 CI behavior), robustness audit module with
+  introduced-codepoint and normalization-stability semantics, render-page tool, and 24 new
+  tests.
+- Quarantined experiment status: unchanged; the U+200C visible-projection experiment was not
+  touched and remains excluded from default, development-release, and CLI paths.
+- Candidate outcome: exploratory partial effectiveness under one fixed condition; primary
+  target failed; NOT product/release admissible (visible-text edits); no overclaim.
+- Deviations: enumerated above; the corpus-generation platform sensitivity is the most
+  significant reproducibility limitation.
+
+## Reproducibility
+
+Full suite at final state: `python -m pytest -o addopts=` -> 1415 passed, 8 skipped, 1 failed
+(`test_frozen_revision_2_spec_is_exact`, the pre-existing Windows CRLF-only `spec.md` freeze
+assertion documented in PR #80; `git show HEAD:spec.md` hashes exactly to the pinned value).
+`git diff --check` clean. Artifact SHA-256 manifest: `artifacts-SHA256SUMS.txt` in this
+directory. Environment: Python 3.11.15, torch 2.13.0+cpu, transformers 5.16.0.dev0 at the
+pinned git commit, Windows-10-10.0.26220.
+
+## Permitted conclusion, precisely
+
+Under the fixed Hugging Face SynthID weighted-mean open detector with public development keys
+and the uncleaned text-only input path, at the pre-registered frozen threshold, the budget-16
+key-blind coverage profile reduced watermarked detection from 63/64 to 11/64 on a new,
+source-disjoint 64-source confirmation corpus while passing all pre-registered fidelity,
+representation, normalization, and rendering gates. It did not reach zero detection. Nothing in
+this cycle demonstrates watermark removal, undetectability, robustness against input cleaning,
+unknown keys, proprietary detectors, or release readiness.
diff --git a/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest-2.json b/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest-2.json
new file mode 100644
index 00000000..4821bb29
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest-2.json
@@ -0,0 +1,1030 @@
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diff --git a/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest.json b/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest.json
new file mode 100644
index 00000000..cf53a892
--- /dev/null
+++ b/evidence/budget-scaled-coverage-2026-08-22/rendering-manifest.json
@@ -0,0 +1,1030 @@
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+      "transformed_text_hash": "d3e26a7c91922b0cc0f78e88551d2bf65026e39d72bbd4bf1527f9f61343f5ba",
+      "variant_hash": "ef0a18812a4c9e7c8df488057ca29dc175282acffe75c66c8e88d6feb902f91c"
+    },
+    {
+      "pair_index": 127,
+      "requested_budget": 16,
+      "source_sample_id": "tiny-dev-attack_development-technical_explanation-40-watermarked",
+      "source_text_hash": "b3d351fbb6710b347298cfe6848d1aa16861865e4577a6f05de46e92c825515d",
+      "transformed_text_hash": "1bf4b9649fc65c6b4a558d408b02486ef7fd2a7a70428321028cb22f538ad4ff",
+      "variant_hash": "671bf1aab76e4d27b4069f2d19c9dc425c13b022eb311d84398ac2bea0181da7"
+    }
+  ],
+  "plan_hash": "0cce41214c3e55ee88cb1ca665d0ebf6c6376bea0d0113a3f4ea481049a5199d"
+}
diff --git a/evidence/content-region-coverage-2026-08-23/confirm3-binding-cross-check.json b/evidence/content-region-coverage-2026-08-23/confirm3-binding-cross-check.json
new file mode 100644
index 00000000..739d8189
--- /dev/null
+++ b/evidence/content-region-coverage-2026-08-23/confirm3-binding-cross-check.json
@@ -0,0 +1,69 @@
+{
+  "460000-A": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "460000-B": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "460000-render": true,
+  "460000-robustness": true,
+  "470000-A": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "470000-B": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "470000-render": true,
+  "470000-robustness": true,
+  "480000-A": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "480000-B": {
+    "blind": true,
+    "commit": true,
+    "corus": true,
+    "evidence": true,
+    "fixed_threshold": true,
+    "plan": true,
+    "rows": "128/128"
+  },
+  "480000-render": true,
+  "480000-robustness": true,
+  "calibration_replay": "7a12862c14ab16febc538c152b2c4d51ecda4b2648f9f8b3ec353ef42dc8ea93",
+  "threshold_audit": [
+    0,
+    256
+  ],
+  "threshold_replay": true,
+  "threshold_value": 0.5570987654320988
+}
diff --git a/evidence/content-region-coverage-2026-08-23/cycle3-artifacts-SHA256SUMS.txt b/evidence/content-region-coverage-2026-08-23/cycle3-artifacts-SHA256SUMS.txt
new file mode 100644
index 00000000..229a40d5
--- /dev/null
+++ b/evidence/content-region-coverage-2026-08-23/cycle3-artifacts-SHA256SUMS.txt
@@ -0,0 +1,60 @@
+8ad6cb1dd4e8b3a00a221735fd76b9174651b84c2d61957813a3a6e0b80088f7 *confirm3-binding-cross-check.json
+cafc349e54c5ba7ebc83eb9d39d56969f416f3b2bb6392309d4cfc8081672611 *confirm3-corpus-460000.json
+9ae5d941f594e5825d6dfbcfa181a26e2200b12f4bd8142fb6139f91d8523267 *confirm3-corpus-470000.json
+60631ea2572042a6e18b2060751835bf65769c1b78c60a7a974517185d22bccd *confirm3-corpus-480000.json
+05c2368d2b0cdca6eed2b259ca2bf277b3fa20bc7dcfe9ecb3afc268c034ba8e *confirm3-evidence-A-460000-provenance.json
+a7f3bd18d2aa27a407fbdbc8f56be32cc03e731faa0356cb60dcf540a721c087 *confirm3-evidence-A-460000.json
+23f2b87130012b5bfcedd5542bf3cee0a08765ec49f5b62d4dd34694db107241 *confirm3-evidence-A-470000-provenance.json
+04c14296238e4bc8445310466d78be442d2edcf1e8c12f0f443d40127c4a1808 *confirm3-evidence-A-470000.json
+c0e81029ab0a9a7f17f436bbd1b6b64500adb9aef6c242e0fb72bd12a3708d11 *confirm3-evidence-A-480000-provenance.json
+a21c29fcb9446eb05a24b942754cb06de40ce74af23ec36396d251d159e75cd5 *confirm3-evidence-A-480000.json
+bccaa46f0e13d08f3be8c2cc8dfed0513a3b8adc82866ee31ec7b21b2e35362c *confirm3-evidence-B-460000-provenance.json
+36c3ca15202764aab5e58472984ca059f7a28d91b181322efe846d121787a395 *confirm3-evidence-B-460000.json
+c33ce1c2f305802eb0f936c37d4c07f79c397c58c4370686263fb814bbbb556c *confirm3-evidence-B-470000-provenance.json
+06c9834785b4cdceacfaa5ebb5182e316d4713df3d105d68bc751b8921dd8b46 *confirm3-evidence-B-470000.json
+33f3e522923ba741986d41cc29922ab8a89448b26b474ba321d3af17d9adcdd2 *confirm3-evidence-B-480000-provenance.json
+175803e559da351ea10a7c609a790b100f270559c084b3f5415b28df9cf03e97 *confirm3-evidence-B-480000.json
+ea60b558d22467b5bb2793e871ab63a852f08ff7bd0ca24bf5c41e0a967561d7 *confirm3-plan-A-460000-provenance.json
+bde3e082077584b288ce2622be7b6dca11fcee37916c32a27b6cc8be0a31f647 *confirm3-plan-A-460000.json
+0ee54a3f28307cc567d676ab97b926959ff810239903eb4444dd8f3871b3c60f *confirm3-plan-A-470000-provenance.json
+d08091e1259af5f9957ca678614d517333854a9af2f2138dec32d8fa9837b7ff *confirm3-plan-A-470000.json
+f688ce34d5e1f0fabbd64bfd22351425acbd34535f69e50387d4d0f5b7e97028 *confirm3-plan-A-480000-provenance.json
+023f138f13ef55858ea8f906596ea3918c8a68710b3167fb817785327a11cc9c *confirm3-plan-A-480000.json
+9b94097882131daa8bf08b243332924bee40b9d30eb13c04974f0fffcfde30b7 *confirm3-plan-B-460000-provenance.json
+6c311633ca839122d96ce3f2ad965ccd95a78c60b864e472cda69e6d6e549b54 *confirm3-plan-B-460000.json
+0330e7a4b98e60e4188245bcfb82fc07f2d18ab4803a1a597df1b47baf4aa6c3 *confirm3-plan-B-470000-provenance.json
+07a9688c4abe967c9ad0db055e9f5574134c6ca95dfb7f10f5f3120e2f8ecc47 *confirm3-plan-B-470000.json
+26e08d091bb1291a9d77dcbd4cfef1328a7a01742061b3c1d4c2c5b8fba95acd *confirm3-plan-B-480000-provenance.json
+f974c48e54bc08f8bfed88e71914ec12aed3fce3436c2b2e36b13af91d4ae50d *confirm3-plan-B-480000.json
+e6f38f203666ac68864a9dd959bcf44c8388a7bf1f7d00519bfc59d612f3243e *confirm3-render-manifest-B-460000.json
+ce2481fc83d57ef3134286b649d49bd201868f4894f9148b6b915bc3da233bdd *confirm3-render-manifest-B-470000.json
+3a3573bad79bf5e10055fa3d3c425f8d72ef78bdcbc16ccc2ab13090e34f4721 *confirm3-render-manifest-B-480000.json
+676a736975ba920dc2a22d423822c7e0476ad5a37066ad1433e372d7693c9500 *confirm3-robustness-460000.json
+3404c6f7d52cf529fdaf0db340c6c11854155eec8c0e8296148791d0016ce050 *confirm3-robustness-470000.json
+469448cd4a39e6c73a1919fdca3c232cd7a9f92528802b5c5528efa11c281b99 *confirm3-robustness-480000.json
+5ec923cc0462af4d7e79e62b8fe6ffe3456f8c06c314d8acff3b6c71defee7bf *dev3-corpus-450000.json
+e18c77c18cc33d1a1d5b9f90cc565dfe649b1827514d08c3d64f1b7ff8c4b2b4 *dev3-evidence-A-450000-provenance.json
+d275295629ca9247241a723d50b67853c70fc2988f5521a7b8d21269db5e65b6 *dev3-evidence-A-450000.json
+abe4597f04ab39c7166b0e031885fd7258bed9a604cf39e3f9fd65c3ec2c7b8f *dev3-evidence-B-450000-provenance.json
+d2354dc8c4a2d13c7982557734c5d4086ea65153bd0172bfbbfb0d608f10e3dd *dev3-evidence-B-450000.json
+425bada8bab9b5cb6fa336406754a120dd61acc4412f5fecd82270376b84e41d *dev3-evidence-C-450000-provenance.json
+10f290f556acc85dcfceab1c94ba055eb09268b983d42d7703add81c156df780 *dev3-evidence-C-450000.json
+9a58e96b7469b10e5366732e9158ff3c421120794549ce124488fcd71fe8d707 *dev3-evidence-D-450000-provenance.json
+ab3017eeb7d08bbed3b4cdb7457dd23a4ba6adff22d0354af383ffd1222e167a *dev3-evidence-D-450000.json
+e563703bdabdf866330b0f64cbe06bfbfa5d7b1fd0685a02e8eecf8fa0b55c2a *dev3-holes-A-450000.json
+29f575bc5a74f7a2a32f815d5979650fa62c6843a9f7de0de591d4d3d55caf20 *dev3-holes-B-450000.json
+ea100383c0ad31819d8224aa513b8de35630c5f4555589e10267baeb36f602de *dev3-holes-C-450000.json
+a9e35e3c1afd395799ea05d110751daeedc048f210910784daa7178114d6904f *dev3-holes-D-450000.json
+3ad9d5feabfe9958762cfa72ec1b7364d1775bb6d2296c708280e179eca3c27a *dev3-plan-A-450000-provenance.json
+7c4257d4a09ece0cc53bc5c6529735caadf2fa4d064d21a2f4720f30d211f5ac *dev3-plan-A-450000.json
+d6857024fb97e9c3ed4128f337ecab60a0c2bdb62db5c55db057fd3ca49d65cc *dev3-plan-B-450000-provenance.json
+26f12b91f2d32ba1d3de077bfbccfac6629d2b647f009e348c9d91a956c8debe *dev3-plan-B-450000.json
+1f8abdbe1db531847bbb4b7ab9c2dd81cec180972a005d4437048088f36d0e94 *dev3-plan-C-450000-provenance.json
+60ddaeda97b5f55dff215eb4557dec5f680def2872c1395b7021ff2dc1ec23ad *dev3-plan-C-450000.json
+64eb9d5622b0222566d454d16d24c22d5467dfa8ffcf504f46030e9364d7759f *dev3-plan-D-450000-provenance.json
+0820650766b19917500cd7d94496bc7313b99837b60c9bf179ea7a9bfd21e1cf *dev3-plan-D-450000.json
+99527adb63bcb282a9d64df29cbdae732499f947cd3f520bb2807e789dfad517 *dev3-robustness-450000.json
+b775c7671740eaff8c6fdf608e89689025d232b44e770a9ab010d5e4f7fdcca0 *calibration-corpus-500000.json
+0b1b9e6ead71caf567e1b21bb3996098298aa207ae86db15c07584faaae09f37 *fixed-threshold.json
+1c04bb330363063995433a216c3cbc0306fcfd1535a537ffec0df97c79f4b15d *holes-cycle1-420000.json
+43f09bc58f4e275b5d79f87942de1e72e615e01da9b38b3b3def8b9008a516be *holes-cycle2-440000.json
diff --git a/evidence/content-region-coverage-2026-08-23/final-report.md b/evidence/content-region-coverage-2026-08-23/final-report.md
new file mode 100644
index 00000000..a102d2bd
--- /dev/null
+++ b/evidence/content-region-coverage-2026-08-23/final-report.md
@@ -0,0 +1,129 @@
+# Content-Region Coverage Cycle 3 - Final Research Report (2026-08-23)
+
+## Repository state
+
+- Base `origin/main`: `16e153fdfa3739a88bca9b1559543a10ded2d859` (unchanged upstream; no open PRs).
+- Research branch: `research/content-region-coverage-v1`, child of Cycle-2 HEAD `4ddd84f`.
+- Final HEAD: `77354e68a45aee9b93aa73afe2ddca0db0bffaa7` (confirmation-scoring commit).
+- Nothing pushed at any point. Worktree clean after final commits.
+- Frozen historical identities verified at takeover: B16 profile hash
+  `6ad142262bfb11a714565d7bd43daa859657fe817bdafa9c8dcf0f4884c07512` replays; Cycle-1/2
+  artifacts intact; full suite 1436 passed / 8 skipped with only the pre-documented
+  Windows-only `spec.md` CRLF freeze failure (`git show HEAD:spec.md` hashes to the pin).
+
+## Measurement (Phase A)
+
+- New identity `open-detector-measurement-stability-v1`. Dedicated calibration corpus: 40 new
+  topics x 4 domains x 8 seeds = 1280 unwatermarked 64-token negatives (seed base 500000,
+  artifact `7a12862c...`), prompt/seed/text disjoint from every prior corpus.
+- Frozen threshold: ascending order statistic n - floor(0.01*n) + 1 = 1015 of 1024 calibration
+  scores = **0.5570987654320988**; comparison `>=`; float64; no tie rounding; target FPR 1%.
+- Audit: 0/256 exceedances on the independent audit split (exact 95% binomial interval
+  recorded in the artifact). Calibration exceedances 10/1024 (0.977%). Detector identity
+  bound and matched at every scoring invocation.
+- This replaces per-corpus thresholds (Cycle 1: 0.5585; Cycle 2: 0.5803) with one
+  corpus-independent value; all six confirmation scorings used it.
+- Environment manifest frozen in the contract (Windows-10-10.0.26220 AMD64, Python 3.11.15,
+  torch 2.13.0+cpu, transformers 5.16.0.dev0 pinned git revision, GPT-2 revision pinned).
+  Cross-platform corpus-generation byte-reproducibility is NOT claimed.
+
+## Candidate mechanism and diagnosis chain (Phases B/C)
+
+- Phase B (structural, on consumed Cycle-1/2 artifacts): uncovered observation windows are
+  dominated by lowercase content words (447 across both confirmations), then capitalized
+  content (99) and listed function words in unreachable positions (142); the worst texts are
+  protected numeric runs (correctly unreachable). New `coverage_holes` module reports token
+  counts, per-family candidate counts, achievable/realized coverage, longest uncovered run,
+  lexical categories, protected intersections, density, and redundancy per source.
+- Phase C: one new rule, `GeneralWordSpacingRule` (`surface-space-after-any-word`): any
+  standalone alphabetic word followed by a single space and a non-space character gains one
+  trailing space. No word list, no hidden representation, case-sensitive, protected spans
+  rejected by the registry. Profile `content-region-coverage-v1` (hashes in the contract),
+  budget 16, unchanged COVERAGE_GREEDY_KEY_BLIND scheduler, seed base 1_150_000.
+- Structural dev evidence: mean achievable coverage 0.841 (Cycle-2 ruleset) -> 0.941
+  (candidate); in the 8 lowest-coverage sources the paired gain was +0.20 (gate >= 0.05);
+  pools 21.6 -> 45.0; zero-candidate rate 0. Ablation: the general rule alone reproduces the
+  full gain (arm C); adding the Cycle-2 word list (arm D) adds candidates but zero coverage -
+  the general rule is the operative mechanism.
+
+## Development (fresh corpus 450000, four detector-blind arms, per-corpus thresholds)
+
+All four arms: 1/32 transformed-watermarked detections (same source), 0/32 unwatermarked
+false positives, fidelity gates 256/256 rows pass. Promotion gate: all twelve criteria
+passed and recorded before confirmation scoring (freeze appendix).
+
+## Confirmation (three frozen corpora, paired A/B, fixed threshold, scored once each)
+
+| Corpus | Pristine WM | A (Cycle-2 ruleset) | B (Cycle-3 candidate) | FP A | FP B |
+| --- | --- | --- | --- | --- | --- |
+| 460000 | 63/64 | 4/64 | 3/64 | 1/64 | 0/64 |
+| 470000 | 64/64 | 8/64 | 7/64 | 1/64 | 1/64 |
+| 480000 | 63/64 | 10/64 | 2/64 | 0/64 | 0/64 |
+| Pooled | 190/192 | 22/192 (11.5%) | 12/192 (6.3%) | 2/192 | 1/192 |
+
+B is paired-better on every corpus and pooled (relative reduction 45%). Mean watermarked
+score drop: B 0.119 vs A 0.113. Margin bands (pooled, B): 9 within +-0.005, 21 within
++-0.010, 51 within +-0.025 of threshold - residual detection remains margin-driven.
+Fidelity/representation gates: 256/256 rows per corpus across both arms. Cross-corpus
+text-hash disjointness: pairwise zero among the three corpora; one naturally occurring
+collision between 480000 and the consumed Cycle-2 corpus 440000 (single degenerate text,
+policy followed: scored as generated, no regeneration). DOM text equality 384/384 pairs;
+screenshot archived.
+
+## Adverse findings (all reported)
+
+1. Currency protected-span extractor bug: a double space before `$100` changed the extracted
+   span from "$100" to " $100" (`PROTECTED_CONTENT_CHANGED`), failing plan A on corpus 480000
+   fail-closed before any scoring. Root cause fixed (whitespace branch now requires a sign),
+   regression tests added, recorded as pre-score amendment 1. The fail-closed builder worked
+   as designed.
+2. Transformed-unwatermarked false positives: 3 events across 384 arm-corpus cells
+   (A: 460000 one, 470000 one; B: 470000 one). Two of the three texts were already above the
+   threshold when pristine (consistent with the fixed threshold's nominal 1% FPR; the 0/64
+   gate was calibrated under the old higher per-corpus thresholds). Two genuine
+   transformation-induced crossings exist (A 0.5234->0.5611; B 0.4510->0.5589, a 0.1079 score
+   increase on an unwatermarked text). The pre-registered 0/64 FP gate FAILED for arm A on
+   460000/470000 and arm B on 470000 and is reported as such.
+3. Degenerate generation events: one all-EOS continuation crash path fixed with deterministic
+   retry in the v3 and calibration generators (pre-scoring); one cross-corpus degenerate text
+   collision (above).
+4. Dev underpredicted absolute residual rates again (1/32 dev vs 12/192 pooled
+   confirmation for arm B).
+
+## Classification
+
+**PARTIAL_SUCCESS** (pre-registered class): the candidate is paired-better than the Cycle-2
+baseline on every confirmation corpus and pooled (22/192 -> 12/192), all structural
+mechanism gates passed, all fidelity gates passed, and pristine-watermark control gates
+passed on all three corpora (63, 64, 63 of 64) - but residual detections remain (12/192, not
+the 0/192 stretch) and the transformed-unwatermarked 0/64 gate failed in three arm-corpus
+cells under the fixed 1%-FPR threshold.
+
+## Permitted conclusion
+
+Under the fixed open Hugging Face SynthID weighted-mean detector with public development
+keys, a frozen corpus-independent threshold at nominal 1% FPR (audit 0/256), and the
+uncleaned text-only input path, a detector-blind key-blind general any-word spacing rule
+materially increased legal candidate coverage in content-word regions and reduced pooled
+transformed watermarked detection from 22/192 to 12/192 relative to the Cycle-2 ruleset in a
+paired three-corpus design, while preserving every fidelity, representation, normalization,
+and rendering gate. The evidence does not establish zero detection, watermark removal,
+undetectability, unknown-key or proprietary-detector performance, cleaning durability, or
+release readiness, and the fixed-threshold regime exhibits expected low-rate false positives
+on unwatermarked text.
+
+## Not supported
+
+Watermark removal; undetectability; SynthID defeat; Gemini or proprietary-detector transfer;
+unknown-key transfer; normalization/cleaning durability; human semantic equivalence (blind
+human fidelity evidence: NOT_PROVIDED); production readiness or release authorization;
+cross-platform byte-reproducible corpus generation.
+
+## Reproducibility
+
+Independent binding cross-check over all Cycle-3 artifacts: every corpus, calibration,
+threshold, plan, evidence, robustness, and render-manifest hash replays and mutually binds;
+128/128 row hashes in all six evidence files; all plans bind the scoring commit and record
+detector_access_observed=false / secret_access_observed=false. Full suite: 1436 passed,
+8 skipped, 1 pre-documented environmental failure. `git diff --check` clean. Artifact
+SHA-256 manifest in this directory; local commits only, nothing pushed, main untouched.
diff --git a/fuckmark/corpus/__init__.py b/fuckmark/corpus/__init__.py
index 1166bd81..73ebc2b3 100644
--- a/fuckmark/corpus/__init__.py
+++ b/fuckmark/corpus/__init__.py
@@ -38,6 +38,21 @@
     load_tiny_dev_corpus_json,
     parse_tiny_dev_corpus_json,
 )
+from .tiny_dev_v3 import (
+    TINY_DEV_V3_CORPUS_ALGORITHM_VERSION,
+    TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN,
+    TinyDevV3CorpusArtifact,
+    build_tiny_dev_v3_corpus,
+)
+from .tiny_dev_v3_generation import (
+    build_real_tiny_dev_v3_corpus,
+    build_tiny_dev_v3_prompt_records,
+)
+from .tiny_dev_io_v3 import (
+    load_tiny_dev_corpus_by_version_json,
+    load_tiny_dev_v3_corpus_json,
+    parse_tiny_dev_v3_corpus_json,
+)
 from .tokenization import GenerationTokenRecord, TextOnlyTokenRecord, TokenTrack
 from .mid_dev_calibration_independence_v3 import (
     MID_DEV_CALIBRATION_INDEPENDENCE_V3_SELECTION_RULE,
@@ -78,6 +93,8 @@
     "TINY_DEV_JSON_MAX_BYTES",
     "TINY_DEV_SPLITS",
     "TINY_DEV_TARGET_LENGTH",
+    "TINY_DEV_V3_CORPUS_ALGORITHM_VERSION",
+    "TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN",
     "CorpusDomain",
     "CorpusIntegrityError",
     "CorpusLeakageError",
@@ -107,14 +124,20 @@
     "TinyDevCorpusCell",
     "TinyDevCorpusError",
     "TinyDevCorpusJsonError",
+    "TinyDevV3CorpusArtifact",
     "TokenTrack",
     "WatermarkCondition",
     "WatermarkLabel",
     "build_corpus_manifest",
     "build_calibration_independence_v3",
     "build_calibration_independence_v3_from_samples",
+    "build_real_tiny_dev_v3_corpus",
     "build_tiny_dev_corpus",
+    "build_tiny_dev_v3_corpus",
+    "build_tiny_dev_v3_prompt_records",
     "load_tiny_dev_corpus_json",
+    "load_tiny_dev_corpus_by_version_json",
+    "load_tiny_dev_v3_corpus_json",
     "load_mid_dev_calibration_independence_v3_artifact_json",
     "load_mid_dev_calibration_independence_v3_exclusion_json",
     "load_mid_dev_calibration_independence_v3_manifest_json",
@@ -122,4 +145,5 @@
     "parse_mid_dev_calibration_independence_v3_exclusion_json",
     "parse_mid_dev_calibration_independence_v3_manifest_json",
     "parse_tiny_dev_corpus_json",
+    "parse_tiny_dev_v3_corpus_json",
 ]
diff --git a/fuckmark/corpus/measurement_calibration.py b/fuckmark/corpus/measurement_calibration.py
new file mode 100644
index 00000000..16cb752d
--- /dev/null
+++ b/fuckmark/corpus/measurement_calibration.py
@@ -0,0 +1,313 @@
+from __future__ import annotations
+
+from collections import defaultdict
+from collections.abc import Sequence
+from dataclasses import dataclass
+
+from .._validation import require_clean_string, require_int, require_sha256
+from ..hashing import sha256_json
+from .prompt import PromptRecord
+from .sample import CorpusSample
+from .schema import CorpusDomain, CorpusSplit, KeySplit, WatermarkLabel
+from .tiny_dev import TINY_DEV_DOMAINS, TINY_DEV_TARGET_LENGTH, TinyDevCorpusError
+
+
+MEASUREMENT_CALIBRATION_CORPUS_VERSION = "measurement-calibration-corpus-v1"
+MEASUREMENT_CALIBRATION_MANIFEST_VERSION = "measurement-calibration-manifest-v1"
+MEASUREMENT_CALIBRATION_PROMPT_SOURCE_ID = "fuckmark-measurement-calibration-prompts-v1"
+MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN = 40
+MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT = 8
+MEASUREMENT_CALIBRATION_SAMPLE_COUNT = (
+    MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN
+    * len(TINY_DEV_DOMAINS)
+    * MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT
+)
+MEASUREMENT_CALIBRATION_NEGATIVE_COUNT = 1024
+MEASUREMENT_CALIBRATION_AUDIT_COUNT = (
+    MEASUREMENT_CALIBRATION_SAMPLE_COUNT - MEASUREMENT_CALIBRATION_NEGATIVE_COUNT
+)
+
+
+_MEASUREMENT_CALIBRATION_TOPICS = (
+    "artifact retention",
+    "audit trails",
+    "binary outcomes",
+    "blinding procedures",
+    "carryover effects",
+    "categorical drift",
+    "causal language",
+    "censoring rules",
+    "checklist discipline",
+    "codebook stability",
+    "cohort definitions",
+    "comparison validity",
+    "compute budgets",
+    "concept drift",
+    "consent records",
+    "contamination checks",
+    "data dictionaries",
+    "decision rules",
+    "definitional clarity",
+    "distribution shift",
+    "documentation debt",
+    "effect direction",
+    "endpoint choice",
+    "enumeration order",
+    "exclusion criteria",
+    "external validity",
+    "fair comparison",
+    "follow-up windows",
+    "group assignment",
+    "hypothesis registries",
+    "inclusion criteria",
+    "interrater agreement",
+    "label leakage",
+    "latent confounding",
+    "lookup tables",
+    "matching strategies",
+    "metadata quality",
+    "missingness patterns",
+    "operationalization",
+    "ownership boundaries",
+)
+
+
+def measurement_calibration_topics() -> tuple[str, ...]:
+    return _MEASUREMENT_CALIBRATION_TOPICS
+
+
+@dataclass(frozen=True, slots=True)
+class MeasurementCalibrationManifest:
+    algorithm_version: str
+    corpus_id: str
+    language: str
+    prompts: tuple[PromptRecord, ...]
+    samples: tuple[CorpusSample, ...]
+    prompt_manifest_hash: str
+    sample_manifest_hash: str
+    manifest_hash: str
+
+    def __post_init__(self) -> None:
+        require_clean_string("algorithm_version", self.algorithm_version)
+        if self.algorithm_version != MEASUREMENT_CALIBRATION_MANIFEST_VERSION:
+            raise ValueError("unsupported measurement calibration manifest version")
+        require_clean_string("corpus_id", self.corpus_id)
+        require_clean_string("language", self.language)
+        if not isinstance(self.prompts, tuple) or not isinstance(self.samples, tuple):
+            raise TypeError("prompts and samples must be tuples")
+        _validate_measurement_calibration_manifest(self)
+        for name in (
+            "prompt_manifest_hash",
+            "sample_manifest_hash",
+            "manifest_hash",
+        ):
+            require_sha256(name, getattr(self, name))
+        payload = {
+            "algorithm_version": self.algorithm_version,
+            "corpus_id": self.corpus_id,
+            "language": self.language,
+            "prompt_manifest_hash": self.prompt_manifest_hash,
+            "sample_manifest_hash": self.sample_manifest_hash,
+            "sample_count": len(self.samples),
+        }
+        if self.manifest_hash != sha256_json(payload):
+            raise ValueError("manifest_hash does not match measurement calibration manifest")
+
+    def payload(self) -> dict[str, object]:
+        return {
+            "algorithm_version": self.algorithm_version,
+            "corpus_id": self.corpus_id,
+            "language": self.language,
+            "prompts": self.prompts,
+            "samples": self.samples,
+            "prompt_manifest_hash": self.prompt_manifest_hash,
+            "sample_manifest_hash": self.sample_manifest_hash,
+            "manifest_hash": self.manifest_hash,
+        }
+
+
+def build_measurement_calibration_manifest(
+    corpus_id: str,
+    prompts: Sequence[PromptRecord],
+    samples: Sequence[CorpusSample],
+    language: str = "en",
+) -> MeasurementCalibrationManifest:
+    require_clean_string("corpus_id", corpus_id)
+    prompt_tuple = tuple(sorted(prompts, key=lambda value: value.prompt_id))
+    sample_tuple = tuple(sorted(samples, key=lambda value: value.sample_id))
+    prompt_manifest_hash = sha256_json(tuple(value.record_hash for value in prompt_tuple))
+    sample_manifest_hash = sha256_json(tuple(value.record_hash for value in sample_tuple))
+    payload = {
+        "algorithm_version": MEASUREMENT_CALIBRATION_MANIFEST_VERSION,
+        "corpus_id": corpus_id,
+        "language": language,
+        "prompt_manifest_hash": prompt_manifest_hash,
+        "sample_manifest_hash": sample_manifest_hash,
+        "sample_count": len(sample_tuple),
+    }
+    return MeasurementCalibrationManifest(
+        algorithm_version=MEASUREMENT_CALIBRATION_MANIFEST_VERSION,
+        corpus_id=corpus_id,
+        language=language,
+        prompts=prompt_tuple,
+        samples=sample_tuple,
+        prompt_manifest_hash=prompt_manifest_hash,
+        sample_manifest_hash=sample_manifest_hash,
+        manifest_hash=sha256_json(payload),
+    )
+
+
+@dataclass(frozen=True, slots=True)
+class MeasurementCalibrationCorpus:
+    algorithm_version: str
+    manifest: MeasurementCalibrationManifest
+    target_length: int
+    topic_count_per_domain: int
+    seeds_per_prompt: int
+    sample_count: int
+    negative_count: int
+    audit_count: int
+    model_identity_hash: str
+    generation_matching_signature_hash: str
+    watermark_condition_hash: str
+    artifact_hash: str
+
+    def __post_init__(self) -> None:
+        require_clean_string("algorithm_version", self.algorithm_version)
+        if self.algorithm_version != MEASUREMENT_CALIBRATION_CORPUS_VERSION:
+            raise ValueError("unsupported measurement calibration corpus version")
+        if not isinstance(self.manifest, MeasurementCalibrationManifest):
+            raise TypeError("manifest must be a MeasurementCalibrationManifest")
+        if self.target_length != TINY_DEV_TARGET_LENGTH:
+            raise ValueError("measurement calibration target length must be 64")
+        if self.topic_count_per_domain != MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN:
+            raise ValueError("measurement calibration topic count is frozen")
+        if self.seeds_per_prompt != MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT:
+            raise ValueError("measurement calibration seed count is frozen")
+        if self.sample_count != MEASUREMENT_CALIBRATION_SAMPLE_COUNT:
+            raise ValueError("measurement calibration sample count is frozen")
+        if self.negative_count != MEASUREMENT_CALIBRATION_NEGATIVE_COUNT:
+            raise ValueError("measurement calibration negative count is frozen")
+        if self.audit_count != MEASUREMENT_CALIBRATION_AUDIT_COUNT:
+            raise ValueError("measurement calibration audit count is frozen")
+        for name in (
+            "model_identity_hash",
+            "generation_matching_signature_hash",
+            "watermark_condition_hash",
+            "artifact_hash",
+        ):
+            require_sha256(name, getattr(self, name))
+        _validate_measurement_calibration_manifest(self.manifest)
+        payload = self._payload()
+        if self.artifact_hash != sha256_json(payload):
+            raise ValueError("artifact_hash does not match measurement calibration corpus")
+
+    def _payload(self) -> dict[str, object]:
+        return {
+            "algorithm_version": self.algorithm_version,
+            "manifest_hash": self.manifest.manifest_hash,
+            "target_length": self.target_length,
+            "topic_count_per_domain": self.topic_count_per_domain,
+            "seeds_per_prompt": self.seeds_per_prompt,
+            "sample_count": self.sample_count,
+            "negative_count": self.negative_count,
+            "audit_count": self.audit_count,
+            "model_identity_hash": self.model_identity_hash,
+            "generation_matching_signature_hash": self.generation_matching_signature_hash,
+            "watermark_condition_hash": self.watermark_condition_hash,
+        }
+
+    def calibration_samples(self) -> tuple[CorpusSample, ...]:
+        ordered = tuple(sorted(self.manifest.samples, key=lambda sample: sample.sample_id))
+        return ordered[: self.negative_count]
+
+    def audit_samples(self) -> tuple[CorpusSample, ...]:
+        ordered = tuple(sorted(self.manifest.samples, key=lambda sample: sample.sample_id))
+        return ordered[self.negative_count :]
+
+
+def _validate_measurement_calibration_manifest(manifest: MeasurementCalibrationManifest) -> None:
+    prompts = manifest.prompts
+    samples = manifest.samples
+    if len(samples) != MEASUREMENT_CALIBRATION_SAMPLE_COUNT:
+        raise TinyDevCorpusError(
+            f"measurement calibration corpus must contain exactly {MEASUREMENT_CALIBRATION_SAMPLE_COUNT} samples"
+        )
+    prompt_ids = tuple(value.prompt_id for value in prompts)
+    if len(set(prompt_ids)) != len(prompt_ids):
+        raise TinyDevCorpusError("measurement calibration prompt IDs must be unique")
+    prompt_texts = tuple(value.text for value in prompts)
+    if len(set(prompt_texts)) != len(prompt_texts):
+        raise TinyDevCorpusError("measurement calibration prompt texts must be unique")
+    family_splits: dict[str, set[CorpusSplit]] = defaultdict(set)
+    for prompt in prompts:
+        family_splits[prompt.prompt_family_id].add(prompt.split)
+    if any(len(splits) != 1 for splits in family_splits.values()):
+        raise TinyDevCorpusError("measurement calibration prompt families must not cross splits")
+    if any(sample.split is not CorpusSplit.THRESHOLD_CALIBRATION for sample in samples):
+        raise TinyDevCorpusError("measurement calibration samples must use the calibration split")
+    if any(sample.label is not WatermarkLabel.UNWATERMARKED for sample in samples):
+        raise TinyDevCorpusError("measurement calibration samples must be unwatermarked")
+    if any(sample.watermark.key_split is not KeySplit.DEV for sample in samples):
+        raise TinyDevCorpusError("measurement calibration samples must record DEV key split")
+    if any(sample.target_length != TINY_DEV_TARGET_LENGTH for sample in samples):
+        raise TinyDevCorpusError("measurement calibration samples must target 64 continuation tokens")
+    domains = {sample.domain for sample in samples}
+    if domains != set(TINY_DEV_DOMAINS):
+        raise TinyDevCorpusError("measurement calibration must cover the frozen four-domain profile")
+    if len({sample.sample_id for sample in samples}) != len(samples):
+        raise TinyDevCorpusError("measurement calibration sample IDs must be unique")
+    if len({sample.text_sha256 for sample in samples}) != len(samples):
+        raise TinyDevCorpusError("measurement calibration texts must be unique")
+    if len({sample.generation_tokens.continuation_token_hash for sample in samples}) != len(samples):
+        raise TinyDevCorpusError("measurement calibration continuations must be unique")
+    prompt_by_id = {value.prompt_id: value for value in prompts}
+    for sample in samples:
+        prompt = prompt_by_id.get(sample.prompt_id)
+        if prompt is None:
+            raise TinyDevCorpusError("measurement calibration sample references an unknown prompt")
+        if sample.prompt_family_id != prompt.prompt_family_id or sample.domain is not prompt.domain:
+            raise TinyDevCorpusError("measurement calibration sample metadata does not match its prompt")
+    if len(set(prompt_by_id) - {sample.prompt_id for sample in samples}):
+        raise TinyDevCorpusError("measurement calibration manifest contains unused prompts")
+
+
+def build_measurement_calibration_corpus(
+    corpus_id: str,
+    prompts: Sequence[PromptRecord],
+    samples: Sequence[CorpusSample],
+) -> MeasurementCalibrationCorpus:
+    require_clean_string("corpus_id", corpus_id)
+    manifest = build_measurement_calibration_manifest(corpus_id, prompts, samples)
+    model_hashes = {sample.model.identity_hash for sample in manifest.samples}
+    generation_hashes = {sample.generation.matching_signature_hash for sample in manifest.samples}
+    watermark_hashes = {sample.watermark.condition_hash for sample in manifest.samples}
+    if len(model_hashes) != 1 or len(generation_hashes) != 1 or len(watermark_hashes) != 1:
+        raise TinyDevCorpusError("measurement calibration must use exactly one identity triple")
+    payload = {
+        "algorithm_version": MEASUREMENT_CALIBRATION_CORPUS_VERSION,
+        "manifest_hash": manifest.manifest_hash,
+        "target_length": TINY_DEV_TARGET_LENGTH,
+        "topic_count_per_domain": MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN,
+        "seeds_per_prompt": MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT,
+        "sample_count": len(manifest.samples),
+        "negative_count": MEASUREMENT_CALIBRATION_NEGATIVE_COUNT,
+        "audit_count": MEASUREMENT_CALIBRATION_AUDIT_COUNT,
+        "model_identity_hash": next(iter(model_hashes)),
+        "generation_matching_signature_hash": next(iter(generation_hashes)),
+        "watermark_condition_hash": next(iter(watermark_hashes)),
+    }
+    return MeasurementCalibrationCorpus(
+        algorithm_version=MEASUREMENT_CALIBRATION_CORPUS_VERSION,
+        manifest=manifest,
+        target_length=TINY_DEV_TARGET_LENGTH,
+        topic_count_per_domain=MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN,
+        seeds_per_prompt=MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT,
+        sample_count=len(manifest.samples),
+        negative_count=MEASUREMENT_CALIBRATION_NEGATIVE_COUNT,
+        audit_count=MEASUREMENT_CALIBRATION_AUDIT_COUNT,
+        model_identity_hash=next(iter(model_hashes)),
+        generation_matching_signature_hash=next(iter(generation_hashes)),
+        watermark_condition_hash=next(iter(watermark_hashes)),
+        artifact_hash=sha256_json(payload),
+    )
diff --git a/fuckmark/corpus/measurement_calibration_io.py b/fuckmark/corpus/measurement_calibration_io.py
new file mode 100644
index 00000000..9dde2d2a
--- /dev/null
+++ b/fuckmark/corpus/measurement_calibration_io.py
@@ -0,0 +1,115 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from ..config import canonical_json_text
+from .prompt import PromptRecord
+from .sample import CorpusSample
+from .tiny_dev_io import (
+    TinyDevCorpusJsonError,
+    _array,
+    _mapping,
+    _prompt,
+    _reject_constant,
+    _sample,
+    _unique_object,
+)
+from .measurement_calibration import (
+    MEASUREMENT_CALIBRATION_MANIFEST_VERSION,
+    MeasurementCalibrationCorpus,
+    MeasurementCalibrationManifest,
+)
+
+
+def _manifest(value: object) -> MeasurementCalibrationManifest:
+    data = _mapping(
+        "manifest",
+        value,
+        (
+            "algorithm_version",
+            "corpus_id",
+            "language",
+            "prompts",
+            "samples",
+            "prompt_manifest_hash",
+            "sample_manifest_hash",
+            "manifest_hash",
+        ),
+    )
+    return MeasurementCalibrationManifest(
+        algorithm_version=data["algorithm_version"],
+        corpus_id=data["corpus_id"],
+        language=data["language"],
+        prompts=tuple(_prompt(item) for item in _array("manifest.prompts", data["prompts"])),
+        samples=tuple(_sample(item) for item in _array("manifest.samples", data["samples"])),
+        prompt_manifest_hash=data["prompt_manifest_hash"],
+        sample_manifest_hash=data["sample_manifest_hash"],
+        manifest_hash=data["manifest_hash"],
+    )
+
+
+def parse_measurement_calibration_corpus_json(
+    text: str,
+    *,
+    require_canonical: bool = True,
+) -> MeasurementCalibrationCorpus:
+    if not isinstance(text, str):
+        raise TypeError("text must be a string")
+    try:
+        decoded = json.loads(
+            text,
+            object_pairs_hook=_unique_object,
+            parse_constant=_reject_constant,
+        )
+    except (json.JSONDecodeError, UnicodeError) as error:
+        raise TinyDevCorpusJsonError("measurement calibration JSON is not valid JSON") from error
+    data = _mapping(
+        "artifact",
+        decoded,
+        (
+            "algorithm_version",
+            "manifest",
+            "target_length",
+            "topic_count_per_domain",
+            "seeds_per_prompt",
+            "sample_count",
+            "negative_count",
+            "audit_count",
+            "model_identity_hash",
+            "generation_matching_signature_hash",
+            "watermark_condition_hash",
+            "artifact_hash",
+        ),
+    )
+    artifact = MeasurementCalibrationCorpus(
+        algorithm_version=data["algorithm_version"],
+        manifest=_manifest(data["manifest"]),
+        target_length=data["target_length"],
+        topic_count_per_domain=data["topic_count_per_domain"],
+        seeds_per_prompt=data["seeds_per_prompt"],
+        sample_count=data["sample_count"],
+        negative_count=data["negative_count"],
+        audit_count=data["audit_count"],
+        model_identity_hash=data["model_identity_hash"],
+        generation_matching_signature_hash=data["generation_matching_signature_hash"],
+        watermark_condition_hash=data["watermark_condition_hash"],
+        artifact_hash=data["artifact_hash"],
+    )
+    if require_canonical:
+        canonical = canonical_json_text(artifact)
+        if text not in (canonical, canonical + "\n"):
+            raise TinyDevCorpusJsonError("measurement calibration JSON is not canonical")
+    return artifact
+
+
+def load_measurement_calibration_corpus_json(
+    path: str | Path,
+    *,
+    require_canonical: bool = True,
+) -> MeasurementCalibrationCorpus:
+    file_path = Path(path)
+    return parse_measurement_calibration_corpus_json(
+        file_path.read_text(encoding="utf-8"),
+        require_canonical=require_canonical,
+    )
diff --git a/fuckmark/corpus/tiny_dev_io_v3.py b/fuckmark/corpus/tiny_dev_io_v3.py
new file mode 100644
index 00000000..59c0306c
--- /dev/null
+++ b/fuckmark/corpus/tiny_dev_io_v3.py
@@ -0,0 +1,132 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from ..config import canonical_json_text
+from .schema import CorpusDomain, CorpusSplit
+from .tiny_dev_io import (
+    TINY_DEV_JSON_MAX_BYTES,
+    TinyDevCorpusJsonError,
+    _array,
+    _manifest,
+    _mapping,
+    _reject_constant,
+    _unique_object,
+)
+from .tiny_dev import TinyDevCorpusError
+from .tiny_dev_v3 import (
+    TINY_DEV_V3_CORPUS_ALGORITHM_VERSION,
+    TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN,
+    TinyDevV3CorpusArtifact,
+    TinyDevV3CorpusCell,
+)
+
+
+def _cell(value: object) -> TinyDevV3CorpusCell:
+    data = _mapping("cell", value, ("split", "domain", "pair_count"))
+    return TinyDevV3CorpusCell(
+        split=CorpusSplit(data["split"]),
+        domain=CorpusDomain(data["domain"]),
+        pair_count=data["pair_count"],
+    )
+
+
+def _artifact_v3(value: object) -> TinyDevV3CorpusArtifact:
+    data = _mapping(
+        "artifact",
+        value,
+        (
+            "algorithm_version",
+            "manifest",
+            "target_length",
+            "calibration_pairs_per_domain",
+            "attack_pairs_per_domain",
+            "required_splits",
+            "required_domains",
+            "model_identity_hash",
+            "generation_matching_signature_hash",
+            "watermark_condition_hash",
+            "cells",
+            "artifact_hash",
+        ),
+    )
+    return TinyDevV3CorpusArtifact(
+        algorithm_version=data["algorithm_version"],
+        manifest=_manifest(data["manifest"]),
+        target_length=data["target_length"],
+        calibration_pairs_per_domain=data["calibration_pairs_per_domain"],
+        attack_pairs_per_domain=data["attack_pairs_per_domain"],
+        required_splits=tuple(
+            CorpusSplit(item) for item in _array("artifact.required_splits", data["required_splits"])
+        ),
+        required_domains=tuple(
+            CorpusDomain(item) for item in _array("artifact.required_domains", data["required_domains"])
+        ),
+        model_identity_hash=data["model_identity_hash"],
+        generation_matching_signature_hash=data["generation_matching_signature_hash"],
+        watermark_condition_hash=data["watermark_condition_hash"],
+        cells=tuple(_cell(item) for item in _array("artifact.cells", data["cells"])),
+        artifact_hash=data["artifact_hash"],
+    )
+
+
+def parse_tiny_dev_v3_corpus_json(text: str, *, require_canonical: bool = True) -> TinyDevV3CorpusArtifact:
+    if not isinstance(text, str):
+        raise TypeError("text must be a string")
+    if len(text.encode("utf-8")) > TINY_DEV_JSON_MAX_BYTES:
+        raise TinyDevCorpusJsonError("tiny-dev v3 JSON exceeds the size limit")
+    try:
+        decoded = json.loads(
+            text,
+            object_pairs_hook=_unique_object,
+            parse_constant=_reject_constant,
+        )
+    except TinyDevCorpusJsonError:
+        raise
+    except (json.JSONDecodeError, UnicodeError) as error:
+        raise TinyDevCorpusJsonError("tiny-dev v3 JSON is not valid JSON") from error
+    try:
+        artifact = _artifact_v3(decoded)
+    except (KeyError, TypeError, ValueError) as error:
+        if isinstance(error, TinyDevCorpusJsonError):
+            raise
+        raise TinyDevCorpusJsonError("tiny-dev v3 JSON failed artifact validation") from error
+    if require_canonical:
+        canonical = canonical_json_text(artifact)
+        if text not in (canonical, canonical + "\n"):
+            raise TinyDevCorpusJsonError("tiny-dev v3 JSON is not in canonical serialized form")
+    return artifact
+
+
+def load_tiny_dev_v3_corpus_json(path: str | Path, *, require_canonical: bool = True) -> TinyDevV3CorpusArtifact:
+    if not isinstance(path, (str, Path)):
+        raise TypeError("path must be a string or Path")
+    file_path = Path(path)
+    size = file_path.stat().st_size
+    if size > TINY_DEV_JSON_MAX_BYTES:
+        raise TinyDevCorpusJsonError("tiny-dev v3 JSON exceeds the size limit")
+    try:
+        text = file_path.read_text(encoding="utf-8")
+    except UnicodeDecodeError as error:
+        raise TinyDevCorpusJsonError("tiny-dev v3 JSON must be UTF-8") from error
+    return parse_tiny_dev_v3_corpus_json(text, require_canonical=require_canonical)
+
+
+def load_tiny_dev_corpus_by_version_json(path: str | Path):
+    if not isinstance(path, (str, Path)):
+        raise TypeError("path must be a string or Path")
+    file_path = Path(path)
+    text = file_path.read_text(encoding="utf-8")
+    try:
+        decoded = json.loads(text)
+    except json.JSONDecodeError as error:
+        raise TinyDevCorpusJsonError("tiny-dev corpus JSON is not valid JSON") from error
+    if not isinstance(decoded, dict):
+        raise TinyDevCorpusJsonError("tiny-dev corpus JSON must be an object")
+    version = decoded.get("algorithm_version")
+    if version == TINY_DEV_V3_CORPUS_ALGORITHM_VERSION:
+        return parse_tiny_dev_v3_corpus_json(text)
+    from .tiny_dev_io import parse_tiny_dev_corpus_json
+
+    return parse_tiny_dev_corpus_json(text)
diff --git a/fuckmark/corpus/tiny_dev_v3.py b/fuckmark/corpus/tiny_dev_v3.py
new file mode 100644
index 00000000..dca17b38
--- /dev/null
+++ b/fuckmark/corpus/tiny_dev_v3.py
@@ -0,0 +1,265 @@
+from __future__ import annotations
+
+from collections import Counter
+from collections.abc import Sequence
+from dataclasses import dataclass
+
+from .._validation import require_clean_string, require_int, require_sha256
+from ..hashing import sha256_json
+from .manifest import CorpusManifest, build_corpus_manifest
+from .prompt import PromptRecord
+from .sample import CorpusSample
+from .schema import CorpusDomain, CorpusSplit, KeySplit, TARGET_LENGTHS
+from .tiny_dev import (
+    TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN,
+    TINY_DEV_SPLITS,
+    TINY_DEV_TARGET_LENGTH,
+    TINY_DEV_DOMAINS,
+    TinyDevCorpusError,
+)
+
+
+TINY_DEV_V3_CORPUS_ALGORITHM_VERSION = "tiny-dev-corpus-v3"
+TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN = 16
+
+
+def _validate_attack_pairs_per_domain(attack_pairs_per_domain: int) -> None:
+    require_int("attack_pairs_per_domain", attack_pairs_per_domain)
+    if attack_pairs_per_domain < 1 or attack_pairs_per_domain > TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN:
+        raise TinyDevCorpusError(
+            "v3 attack pairs per domain must lie between 1 and "
+            f"{TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN}"
+        )
+
+
+@dataclass(frozen=True, slots=True)
+class TinyDevV3CorpusCell:
+    split: CorpusSplit
+    domain: CorpusDomain
+    pair_count: int
+
+    def __post_init__(self) -> None:
+        if not isinstance(self.split, CorpusSplit):
+            raise TypeError("split must be a CorpusSplit")
+        if not isinstance(self.domain, CorpusDomain):
+            raise TypeError("domain must be a CorpusDomain")
+        require_int("pair_count", self.pair_count)
+        if self.pair_count < 1:
+            raise ValueError("tiny development v3 corpus cell pair count must be positive")
+
+
+@dataclass(frozen=True, slots=True)
+class TinyDevV3CorpusArtifact:
+    algorithm_version: str
+    manifest: CorpusManifest
+    target_length: int
+    calibration_pairs_per_domain: int
+    attack_pairs_per_domain: int
+    required_splits: tuple[CorpusSplit, ...]
+    required_domains: tuple[CorpusDomain, ...]
+    model_identity_hash: str
+    generation_matching_signature_hash: str
+    watermark_condition_hash: str
+    cells: tuple[TinyDevV3CorpusCell, ...]
+    artifact_hash: str
+
+    def __post_init__(self) -> None:
+        require_clean_string("algorithm_version", self.algorithm_version)
+        if self.algorithm_version != TINY_DEV_V3_CORPUS_ALGORITHM_VERSION:
+            raise ValueError("unsupported tiny development v3 corpus algorithm version")
+        if not isinstance(self.manifest, CorpusManifest):
+            raise TypeError("manifest must be a CorpusManifest")
+        require_int("target_length", self.target_length)
+        if self.target_length != TINY_DEV_TARGET_LENGTH or self.target_length not in TARGET_LENGTHS:
+            raise ValueError("tiny development v3 corpus target length must be 64")
+        require_int("calibration_pairs_per_domain", self.calibration_pairs_per_domain)
+        if self.calibration_pairs_per_domain != TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN:
+            raise ValueError("v3 calibration pair count must match the frozen calibration profile")
+        _validate_attack_pairs_per_domain(self.attack_pairs_per_domain)
+        if self.required_splits != TINY_DEV_SPLITS:
+            raise ValueError("tiny development v3 corpus split profile does not match the frozen profile")
+        if self.required_domains != TINY_DEV_DOMAINS:
+            raise ValueError("tiny development v3 corpus domain profile does not match the frozen profile")
+        require_sha256("model_identity_hash", self.model_identity_hash)
+        require_sha256("generation_matching_signature_hash", self.generation_matching_signature_hash)
+        require_sha256("watermark_condition_hash", self.watermark_condition_hash)
+        if not isinstance(self.cells, tuple):
+            raise TypeError("cells must be a tuple")
+        if any(not isinstance(value, TinyDevV3CorpusCell) for value in self.cells):
+            raise TypeError("cells must contain TinyDevV3CorpusCell values")
+        expected_cells = _expected_v3_cells(self.attack_pairs_per_domain)
+        if self.cells != expected_cells:
+            raise ValueError("tiny development v3 corpus cells do not match the parameterized matrix")
+        _validate_v3_manifest(
+            self.manifest,
+            self.model_identity_hash,
+            self.generation_matching_signature_hash,
+            self.watermark_condition_hash,
+            self.attack_pairs_per_domain,
+        )
+        require_sha256("artifact_hash", self.artifact_hash)
+        if self.artifact_hash != sha256_json(self._payload()):
+            raise ValueError("artifact_hash does not match tiny development v3 corpus artifact")
+
+    def _payload(self) -> dict[str, object]:
+        return {
+            "algorithm_version": self.algorithm_version,
+            "manifest_hash": self.manifest.manifest_hash,
+            "target_length": self.target_length,
+            "calibration_pairs_per_domain": self.calibration_pairs_per_domain,
+            "attack_pairs_per_domain": self.attack_pairs_per_domain,
+            "required_splits": tuple(value.value for value in self.required_splits),
+            "required_domains": tuple(value.value for value in self.required_domains),
+            "model_identity_hash": self.model_identity_hash,
+            "generation_matching_signature_hash": self.generation_matching_signature_hash,
+            "watermark_condition_hash": self.watermark_condition_hash,
+            "cells": self.cells,
+        }
+
+
+def _expected_v3_cells(attack_pairs_per_domain: int) -> tuple[TinyDevV3CorpusCell, ...]:
+    return tuple(
+        TinyDevV3CorpusCell(split, domain, _v3_pairs_for_split(split, attack_pairs_per_domain))
+        for split in TINY_DEV_SPLITS
+        for domain in TINY_DEV_DOMAINS
+    )
+
+
+def _v3_pairs_for_split(split: CorpusSplit, attack_pairs_per_domain: int) -> int:
+    if split is CorpusSplit.THRESHOLD_CALIBRATION:
+        return TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN
+    if split is CorpusSplit.ATTACK_DEVELOPMENT:
+        return attack_pairs_per_domain
+    raise TinyDevCorpusError("split is outside the frozen tiny development profile")
+
+
+def _validate_v3_manifest(
+    manifest: CorpusManifest,
+    model_identity_hash: str,
+    generation_matching_signature_hash: str,
+    watermark_condition_hash: str,
+    attack_pairs_per_domain: int,
+) -> None:
+    prompts = manifest.prompts
+    samples = manifest.samples
+    expected_pair_count = sum(
+        _v3_pairs_for_split(split, attack_pairs_per_domain) * len(TINY_DEV_DOMAINS)
+        for split in TINY_DEV_SPLITS
+    )
+    expected_sample_count = expected_pair_count * 2
+    if len(samples) != expected_sample_count:
+        raise TinyDevCorpusError(
+            f"tiny development v3 corpus must contain exactly {expected_sample_count} samples"
+        )
+    if len({sample.match_id for sample in samples}) != expected_pair_count:
+        raise TinyDevCorpusError(
+            f"tiny development v3 corpus must contain exactly {expected_pair_count} matched pairs"
+        )
+    if len(prompts) != expected_pair_count:
+        raise TinyDevCorpusError("tiny development v3 corpus must contain exactly one prompt per matched pair")
+    allowed_splits = set(TINY_DEV_SPLITS)
+    allowed_domains = set(TINY_DEV_DOMAINS)
+    if any(prompt.split not in allowed_splits for prompt in prompts):
+        raise TinyDevCorpusError("tiny development v3 prompts may use only calibration or attack-development splits")
+    if any(prompt.domain not in allowed_domains for prompt in prompts):
+        raise TinyDevCorpusError("tiny development v3 prompts must use the frozen four-domain profile")
+    if any(sample.split not in allowed_splits for sample in samples):
+        raise TinyDevCorpusError("tiny development v3 samples may use only calibration or attack-development splits")
+    if any(sample.domain not in allowed_domains for sample in samples):
+        raise TinyDevCorpusError("tiny development v3 samples must use the frozen four-domain profile")
+    if any(sample.target_length != TINY_DEV_TARGET_LENGTH for sample in samples):
+        raise TinyDevCorpusError("tiny development v3 samples must target 64 continuation tokens")
+    if any(sample.watermark.key_split is not KeySplit.DEV for sample in samples):
+        raise TinyDevCorpusError("tiny development v3 samples must use DEV_KEYS only")
+    if {sample.model.identity_hash for sample in samples} != {model_identity_hash}:
+        raise TinyDevCorpusError("tiny development v3 corpus must use one frozen model/tokenizer identity")
+    if {sample.generation.matching_signature_hash for sample in samples} != {
+        generation_matching_signature_hash
+    }:
+        raise TinyDevCorpusError("tiny development v3 corpus must use one matched generation-parameter signature")
+    if {sample.watermark.condition_hash for sample in samples} != {watermark_condition_hash}:
+        raise TinyDevCorpusError("tiny development v3 corpus must use one frozen DEV watermark condition")
+    prompt_counts = Counter(sample.prompt_id for sample in samples)
+    if any(prompt_counts[prompt.prompt_id] != 2 for prompt in prompts):
+        raise TinyDevCorpusError("each tiny development v3 prompt must bind exactly one matched on/off pair")
+    cell_pairs: Counter[tuple[CorpusSplit, CorpusDomain]] = Counter()
+    seen_match_ids: set[str] = set()
+    for sample in samples:
+        if sample.match_id in seen_match_ids:
+            continue
+        seen_match_ids.add(sample.match_id)
+        cell_pairs[(sample.split, sample.domain)] += 1
+    expected_cells = {
+        (split, domain): _v3_pairs_for_split(split, attack_pairs_per_domain)
+        for split in TINY_DEV_SPLITS
+        for domain in TINY_DEV_DOMAINS
+    }
+    if dict(cell_pairs) != expected_cells:
+        raise TinyDevCorpusError("tiny development v3 corpus split/domain pair counts do not match the profile")
+    calibration_negatives = sum(
+        1
+        for sample in samples
+        if sample.split is CorpusSplit.THRESHOLD_CALIBRATION
+        and sample.label.value == "unwatermarked"
+    )
+    if calibration_negatives < 100:
+        raise TinyDevCorpusError("tiny development v3 corpus must contain at least 100 calibration negatives")
+
+
+def build_tiny_dev_v3_corpus(
+    corpus_id: str,
+    prompts: Sequence[PromptRecord],
+    samples: Sequence[CorpusSample],
+    *,
+    attack_pairs_per_domain: int,
+) -> TinyDevV3CorpusArtifact:
+    require_clean_string("corpus_id", corpus_id)
+    _validate_attack_pairs_per_domain(attack_pairs_per_domain)
+    manifest = build_corpus_manifest(corpus_id, prompts, samples)
+    model_hashes = {sample.model.identity_hash for sample in manifest.samples}
+    generation_hashes = {sample.generation.matching_signature_hash for sample in manifest.samples}
+    watermark_hashes = {sample.watermark.condition_hash for sample in manifest.samples}
+    if len(model_hashes) != 1:
+        raise TinyDevCorpusError("tiny development v3 corpus must use exactly one model/tokenizer identity")
+    if len(generation_hashes) != 1:
+        raise TinyDevCorpusError("tiny development v3 corpus must use exactly one generation matching signature")
+    if len(watermark_hashes) != 1:
+        raise TinyDevCorpusError("tiny development v3 corpus must use exactly one watermark condition")
+    model_identity_hash = next(iter(model_hashes))
+    generation_matching_signature_hash = next(iter(generation_hashes))
+    watermark_condition_hash = next(iter(watermark_hashes))
+    _validate_v3_manifest(
+        manifest,
+        model_identity_hash,
+        generation_matching_signature_hash,
+        watermark_condition_hash,
+        attack_pairs_per_domain,
+    )
+    cells = _expected_v3_cells(attack_pairs_per_domain)
+    payload = {
+        "algorithm_version": TINY_DEV_V3_CORPUS_ALGORITHM_VERSION,
+        "manifest_hash": manifest.manifest_hash,
+        "target_length": TINY_DEV_TARGET_LENGTH,
+        "calibration_pairs_per_domain": TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN,
+        "attack_pairs_per_domain": attack_pairs_per_domain,
+        "required_splits": tuple(value.value for value in TINY_DEV_SPLITS),
+        "required_domains": tuple(value.value for value in TINY_DEV_DOMAINS),
+        "model_identity_hash": model_identity_hash,
+        "generation_matching_signature_hash": generation_matching_signature_hash,
+        "watermark_condition_hash": watermark_condition_hash,
+        "cells": cells,
+    }
+    return TinyDevV3CorpusArtifact(
+        TINY_DEV_V3_CORPUS_ALGORITHM_VERSION,
+        manifest,
+        TINY_DEV_TARGET_LENGTH,
+        TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN,
+        attack_pairs_per_domain,
+        TINY_DEV_SPLITS,
+        TINY_DEV_DOMAINS,
+        model_identity_hash,
+        generation_matching_signature_hash,
+        watermark_condition_hash,
+        cells,
+        sha256_json(payload),
+    )
diff --git a/fuckmark/corpus/tiny_dev_v3_generation.py b/fuckmark/corpus/tiny_dev_v3_generation.py
new file mode 100644
index 00000000..378837df
--- /dev/null
+++ b/fuckmark/corpus/tiny_dev_v3_generation.py
@@ -0,0 +1,216 @@
+from __future__ import annotations
+
+from ..hashing import sha256_json, sha256_text
+from .prompt import PromptRecord
+from .schema import CorpusDomain, CorpusSplit, KeySplit, MAX_GENERATION_SEED, WatermarkLabel
+from .tiny_dev import (
+    TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN,
+    TINY_DEV_SPLITS,
+    TINY_DEV_TARGET_LENGTH,
+    TinyDevCorpusError,
+)
+from .tiny_dev_generation import (
+    TINY_DEV_DEFAULT_MAX_ATTEMPTS,
+    TINY_DEV_PAIR_SEED_STRIDE,
+    TINY_DEV_PROMPT_LICENSE_ID,
+    TINY_DEV_PROMPT_PROVENANCE,
+    TINY_DEV_PROMPT_SOURCE_ID,
+    TINY_DEV_SEED_POLICY_ID,
+    TinyDevGenerationBackend,
+    TinyDevGenerationError,
+    _TINY_DEV_TEMPLATES,
+    _TINY_DEV_TOPICS,
+    _build_sample,
+)
+from .tiny_dev_v3 import (
+    TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN,
+    TinyDevV3CorpusArtifact,
+    build_tiny_dev_v3_corpus,
+)
+
+
+TINY_DEV_V3_GENERATION_ALGORITHM_VERSION = "tiny-dev-v3-generation-v1"
+TINY_DEV_V3_PROMPT_SOURCE_ID = "fuckmark-tiny-dev-v3-prompts-v1"
+TINY_DEV_V3_DOMAINS = tuple(CorpusDomain)
+
+_TINY_DEV_V3_ATTACK_TOPICS = (
+    "research claims",
+    "effect size honesty",
+    "preregistration discipline",
+    "randomization integrity",
+    "baseline drift",
+    "reporting bias",
+    "measurement error",
+    "replication crisis",
+    "statistical power",
+    "selection effects",
+    "confound control",
+    "outcome switching",
+    "sample size planning",
+    "analysis robustness",
+    "evidence strength",
+    "uncertainty reporting",
+)
+
+
+def _v3_topics() -> tuple[str, ...]:
+    if _TINY_DEV_TOPICS[25] != _TINY_DEV_V3_ATTACK_TOPICS[0]:
+        raise TinyDevCorpusError("v3 attack topic pool must extend the v2 attack topic")
+    return (*_TINY_DEV_TOPICS[:25], *_TINY_DEV_V3_ATTACK_TOPICS)
+
+
+def _v3_prompt_source_hash(attack_pairs_per_domain: int) -> str:
+    return sha256_json(
+        {
+            "algorithm_version": TINY_DEV_V3_GENERATION_ALGORITHM_VERSION,
+            "v2_source_id": TINY_DEV_PROMPT_SOURCE_ID,
+            "source_id": TINY_DEV_V3_PROMPT_SOURCE_ID,
+            "license_id": TINY_DEV_PROMPT_LICENSE_ID,
+            "provenance": TINY_DEV_PROMPT_PROVENANCE,
+            "attack_pairs_per_domain": attack_pairs_per_domain,
+            "calibration_topics": _TINY_DEV_TOPICS[:25],
+            "attack_topics": _TINY_DEV_V3_ATTACK_TOPICS,
+            "templates": tuple(
+                (domain.value, _TINY_DEV_TEMPLATES[domain])
+                for domain in TINY_DEV_V3_DOMAINS
+            ),
+        }
+    )
+
+
+def build_tiny_dev_v3_prompt_records(attack_pairs_per_domain: int) -> tuple[PromptRecord, ...]:
+    if type(attack_pairs_per_domain) is not int or attack_pairs_per_domain < 1:
+        raise ValueError("attack_pairs_per_domain must be a positive integer")
+    if attack_pairs_per_domain > TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN:
+        raise TinyDevCorpusError(
+            "v3 attack pairs per domain exceeds the frozen maximum of "
+            f"{TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN}"
+        )
+    topics = _v3_topics()
+    source_hash = _v3_prompt_source_hash(attack_pairs_per_domain)
+    records: list[PromptRecord] = []
+    for split in TINY_DEV_SPLITS:
+        pair_count = (
+            TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN
+            if split is CorpusSplit.THRESHOLD_CALIBRATION
+            else attack_pairs_per_domain
+        )
+        topic_offset = (
+            0
+            if split is CorpusSplit.THRESHOLD_CALIBRATION
+            else TINY_DEV_CALIBRATION_PAIRS_PER_DOMAIN
+        )
+        for domain in TINY_DEV_V3_DOMAINS:
+            template = _TINY_DEV_TEMPLATES[domain]
+            for local_index in range(pair_count):
+                topic_index = topic_offset + local_index
+                topic = topics[topic_index]
+                prompt_id = f"tiny-dev-{split.value}-{domain.value}-{topic_index:02d}"
+                records.append(
+                    PromptRecord.create(
+                        prompt_id=prompt_id,
+                        prompt_family_id=f"tiny-dev-family-{domain.value}-{topic_index:02d}",
+                        domain=domain,
+                        split=split,
+                        source_id=TINY_DEV_V3_PROMPT_SOURCE_ID,
+                        source_hash=source_hash,
+                        license_id=TINY_DEV_PROMPT_LICENSE_ID,
+                        provenance=TINY_DEV_PROMPT_PROVENANCE,
+                        text=template.format(topic=topic),
+                    )
+                )
+    return tuple(sorted(records, key=lambda value: value.prompt_id))
+
+
+def build_real_tiny_dev_v3_corpus(
+    backend: TinyDevGenerationBackend,
+    *,
+    corpus_id: str = "fuckmark-tiny-dev-real-v3",
+    seed_base: int = 402000,
+    attack_pairs_per_domain: int = 1,
+    max_attempts: int = TINY_DEV_DEFAULT_MAX_ATTEMPTS,
+) -> TinyDevV3CorpusArtifact:
+    if type(seed_base) is not int or seed_base < 0:
+        raise ValueError("seed_base must be a non-negative integer")
+    if type(max_attempts) is not int or max_attempts <= 0:
+        raise ValueError("max_attempts must be a positive integer")
+    if type(attack_pairs_per_domain) is not int or attack_pairs_per_domain < 1:
+        raise ValueError("attack_pairs_per_domain must be a positive integer")
+    if attack_pairs_per_domain > TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN:
+        raise ValueError("attack_pairs_per_domain exceeds the frozen v3 maximum")
+    prompts = build_tiny_dev_v3_prompt_records(attack_pairs_per_domain)
+    if seed_base + len(prompts) * TINY_DEV_PAIR_SEED_STRIDE + max_attempts > MAX_GENERATION_SEED:
+        raise ValueError("seed schedule exceeds the 64-bit generation-seed range")
+
+    samples: list[object] = []
+    seen_text_hashes: set[str] = set()
+    seen_token_hashes: set[str] = set()
+
+    for pair_index, prompt in enumerate(prompts):
+        pair_seed_base = seed_base + pair_index * TINY_DEV_PAIR_SEED_STRIDE
+        accepted = False
+        for attempt in range(max_attempts):
+            seed = pair_seed_base + attempt
+            try:
+                control = backend.generate(prompt.text, seed, watermarked=False)
+                watermarked = backend.generate(prompt.text, seed, watermarked=True)
+            except RuntimeError:
+                continue
+            if not control.text.strip() or not watermarked.text.strip():
+                continue
+            candidates = (
+                (WatermarkLabel.UNWATERMARKED, control),
+                (WatermarkLabel.WATERMARKED, watermarked),
+            )
+            if any(
+                len(value.continuation_token_ids) != TINY_DEV_TARGET_LENGTH
+                for _, value in candidates
+            ):
+                continue
+            text_hashes = tuple(sha256_text(value.text) for _, value in candidates)
+            token_hashes = tuple(
+                sha256_json(value.continuation_token_ids)
+                for _, value in candidates
+            )
+            if len(set(text_hashes)) != len(text_hashes) or len(set(token_hashes)) != len(token_hashes):
+                continue
+            if any(value in seen_text_hashes for value in text_hashes):
+                continue
+            if any(value in seen_token_hashes for value in token_hashes):
+                continue
+            pair_samples = tuple(
+                _build_sample(
+                    prompt=prompt,
+                    label=label,
+                    generated=value,
+                    backend=backend,
+                    seed=seed,
+                )
+                for label, value in candidates
+            )
+            samples.extend(pair_samples)
+            seen_text_hashes.update(text_hashes)
+            seen_token_hashes.update(token_hashes)
+            accepted = True
+            break
+        if not accepted:
+            raise TinyDevGenerationError(
+                f"could not produce an exact, unique 64-token pair for {prompt.prompt_id} "
+                f"within {max_attempts} deterministic attempts"
+            )
+
+    artifact = build_tiny_dev_v3_corpus(
+        corpus_id,
+        prompts,
+        samples,
+        attack_pairs_per_domain=attack_pairs_per_domain,
+    )
+    if any(sample.watermark.key_split is not KeySplit.DEV for sample in artifact.manifest.samples):
+        raise TinyDevGenerationError("real tiny development v3 generation must use DEV_KEYS")
+    for match_id in sorted({sample.match_id for sample in artifact.manifest.samples}):
+        pair = tuple(sample for sample in artifact.manifest.samples if sample.match_id == match_id)
+        if len({sample.generation.seed for sample in pair}) != 1:
+            raise TinyDevGenerationError("real tiny development v3 runner requires one shared seed per on/off pair")
+        if any(sample.generation.seed_policy_id != TINY_DEV_SEED_POLICY_ID for sample in pair):
+            raise TinyDevGenerationError("real tiny development v3 pair seed policy drifted")
+    return artifact
diff --git a/fuckmark/experiments/coverage_holes.py b/fuckmark/experiments/coverage_holes.py
new file mode 100644
index 00000000..eae71e9c
--- /dev/null
+++ b/fuckmark/experiments/coverage_holes.py
@@ -0,0 +1,328 @@
+from __future__ import annotations
+
+from collections import Counter
+from typing import Any
+
+from ..hashing import sha256_json
+from ..transforms.protected import ProtectedSpanExtractor
+
+
+COVERAGE_HOLE_ANALYSIS_VERSION = "coverage-hole-structure-v1"
+NGRAM_LEN = 5
+
+_FUNCTION_WORDS = frozenset(
+    (
+        "is",
+        "of",
+        "to",
+        "the",
+        "and",
+        "in",
+        "for",
+        "on",
+        "with",
+        "as",
+        "from",
+        "that",
+        "this",
+        "was",
+        "are",
+        "be",
+        "can",
+        "will",
+        "have",
+        "has",
+        "not",
+        "but",
+        "or",
+        "by",
+        "at",
+        "it",
+        "we",
+        "you",
+        "they",
+        "an",
+        "he",
+        "she",
+        "his",
+        "her",
+        "its",
+        "our",
+        "their",
+        "them",
+        "him",
+        "us",
+        "me",
+        "my",
+        "your",
+        "if",
+        "when",
+        "where",
+        "which",
+        "who",
+        "what",
+        "how",
+        "why",
+        "because",
+        "so",
+        "than",
+        "then",
+        "there",
+        "here",
+        "all",
+        "any",
+        "each",
+        "more",
+        "most",
+        "some",
+        "such",
+        "only",
+        "very",
+        "just",
+        "also",
+        "into",
+        "about",
+        "over",
+        "under",
+        "after",
+        "before",
+        "between",
+        "during",
+        "through",
+        "without",
+        "while",
+        "do",
+        "does",
+        "been",
+        "being",
+        "would",
+        "could",
+        "should",
+        "may",
+        "might",
+        "must",
+        "were",
+        "one",
+        "even",
+        "still",
+        "often",
+    )
+)
+
+
+def classify_word(word: str) -> str:
+    stripped = word.strip(".,;:!?\"'()")
+    if not stripped:
+        return "punctuation_or_empty"
+    if stripped.isdigit():
+        return "numeric"
+    lowered = stripped.lower()
+    if lowered in _FUNCTION_WORDS:
+        return "function_word"
+    if stripped[0].isupper():
+        return "capitalized_content"
+    if stripped.isalpha():
+        return "lowercase_content"
+    return "other"
+
+
+def _rule_family(rule_id: str) -> str:
+    if rule_id.startswith("contract"):
+        return "contraction"
+    if rule_id.startswith("surface"):
+        return "surface_spacing"
+    if rule_id.startswith("lexical"):
+        return "lexical"
+    if rule_id.startswith("syntax"):
+        return "syntax"
+    return "other"
+
+
+def build_coverage_hole_row(
+    text: str,
+    token_ids: tuple[int, ...],
+    offsets: tuple[tuple[int, int], ...],
+    enumeration,
+    geometry,
+    variant,
+) -> dict[str, object]:
+    token_count = len(token_ids)
+    observation_count = max(0, token_count - NGRAM_LEN + 1)
+    coverage = geometry.coverage_mapping()
+    window_hits = Counter()
+    for candidate_id, intervals in coverage.items():
+        for interval in intervals:
+            for window in range(interval.start, interval.end_exclusive):
+                window_hits[window] += 1
+    uncovered = tuple(w for w in range(observation_count) if window_hits[w] == 0)
+    covered_windows = observation_count - len(uncovered)
+    longest_run = 0
+    run = 0
+    for window in range(observation_count):
+        if window_hits[window] == 0:
+            run += 1
+            longest_run = max(longest_run, run)
+        else:
+            run = 0
+    uncovered_spans = []
+    cursor = None
+    for window in uncovered:
+        if cursor is None or window != cursor[1]:
+            if cursor is not None:
+                uncovered_spans.append(cursor)
+            cursor = [window, window + 1]
+        else:
+            cursor[1] = window + 1
+    if cursor is not None:
+        uncovered_spans.append(cursor)
+    lexical_categories: Counter[str] = Counter()
+    uncovered_word_samples: list[str] = []
+    protected = ProtectedSpanExtractor().extract(text)
+    protected_char_spans = tuple((span.start, span.end) for span in protected.spans)
+    protected_intersections = 0
+    for start_window, end_window in uncovered_spans:
+        char_start = offsets[start_window][0] if start_window < len(offsets) else len(text)
+        char_end = offsets[min(end_window - 1, len(offsets) - 1)][1] if end_window - 1 < len(offsets) else len(text)
+        snippet = text[char_start:char_end]
+        for token in snippet.split():
+            lexical_categories[classify_word(token)] += 1
+        if len(uncovered_word_samples) < 5 and snippet.strip():
+            uncovered_word_samples.append(snippet.strip()[:60])
+        for span_start, span_end in protected_char_spans:
+            if span_start < char_end and char_start < span_end:
+                protected_intersections += 1
+                break
+    selected_ids = set(variant["selected_candidate_ids"])
+    realized_windows = sum(
+        1
+        for window in range(observation_count)
+        if any(
+            interval.start <= window < interval.end_exclusive
+            for candidate_id, intervals in coverage.items()
+            if candidate_id in selected_ids
+            for interval in intervals
+        )
+    )
+    candidate_by_family = Counter(
+        _rule_family(candidate.rule_id) for candidate in enumeration.candidates
+    )
+    redundancy = (
+        sum(window_hits.values()) / covered_windows if covered_windows else 0.0
+    )
+    return {
+        "source_sample_id": variant["source_sample_id"],
+        "source_label": variant["source_label"],
+        "domain": variant["domain"],
+        "token_count": token_count,
+        "observation_window_count": observation_count,
+        "candidate_count": len(enumeration.candidates),
+        "candidate_count_by_family": dict(candidate_by_family),
+        "candidate_density_per_100_tokens": round(100.0 * len(enumeration.candidates) / token_count, 4) if token_count else 0.0,
+        "zero_candidate_source": len(enumeration.candidates) == 0,
+        "achievable_coverage_fraction": covered_windows / observation_count if observation_count else 0.0,
+        "realized_coverage_fraction": realized_windows / observation_count if observation_count else 0.0,
+        "uncovered_window_count": len(uncovered),
+        "longest_uncovered_run": longest_run,
+        "uncovered_span_count": len(uncovered_spans),
+        "uncovered_lexical_categories": dict(lexical_categories),
+        "unprotected_word_samples": uncovered_word_samples,
+        "protected_span_intersections": protected_intersections,
+        "candidate_redundancy_mean_multiplicity": round(redundancy, 4),
+    }
+
+
+def build_coverage_hole_report(corpus: Any, tokenizer: Any, plan: dict[str, object]) -> dict[str, object]:
+    from ..experiments.effectiveness_plan import _attack_samples, _encode_with_offsets
+    from ..transforms import build_candidate_tokenizer_geometry
+
+    registry = _registry_for_plan(plan)
+    profile_budgets = plan["budgets"]
+    sources = {sample.sample_id: sample for sample in _attack_samples(corpus)}
+    rows = []
+    for variant in plan["variants"]:
+        if variant["requested_budget"] != profile_budgets[0]:
+            continue
+        source = sources[variant["source_sample_id"]]
+        token_ids, offsets = _encode_with_offsets(tokenizer, source)
+        enumeration = registry.enumerate(source.text)
+        geometry = build_candidate_tokenizer_geometry(
+            source.text,
+            enumeration,
+            token_ids,
+            offsets,
+            tokenizer_identity_hash=source.model.identity_hash,
+            ngram_len=NGRAM_LEN,
+        )
+        rows.append(
+            build_coverage_hole_row(
+                source.text,
+                token_ids,
+                offsets,
+                enumeration,
+                geometry,
+                variant,
+            )
+        )
+    row_tuple = tuple(rows)
+    watermarked = tuple(row for row in row_tuple if row["source_label"] == "watermarked")
+    aggregated: Counter[str] = Counter()
+    for row in watermarked:
+        for category, count in row["uncovered_lexical_categories"].items():
+            aggregated[category] += count
+    payload = {
+        "algorithm_version": COVERAGE_HOLE_ANALYSIS_VERSION,
+        "analysis_scope": "structural text-geometry diagnosis; no detector information used",
+        "plan_hash": plan["plan_hash"],
+        "ruleset_hash": plan["ruleset_hash"],
+        "rows": row_tuple,
+        "watermarked_uncovered_lexical_totals": dict(aggregated),
+    }
+    return {**payload, "artifact_hash": sha256_json(payload)}
+
+
+def _registry_for_plan(plan: dict[str, object]):
+    from .effectiveness_plan import _registry_for_profile
+    from ..transforms import EffectivenessTransformProfile, resolve_effectiveness_profile
+
+    profile = resolve_effectiveness_profile(plan["profile_id"], tuple(plan["budgets"]))
+    return _registry_for_profile(profile)
+
+
+def main(argv: list[str] | None = None) -> int:
+    import argparse
+    import json
+    import sys
+    from pathlib import Path
+
+    parser = argparse.ArgumentParser(prog="fuckmark-coverage-holes")
+    parser.add_argument("--corpus-json", type=Path, required=True)
+    parser.add_argument("--plan-json", type=Path, required=True)
+    parser.add_argument("--json", type=Path, required=True)
+    args = parser.parse_args(argv)
+    from ..corpus import load_tiny_dev_corpus_by_version_json
+
+    corpus = load_tiny_dev_corpus_by_version_json(args.corpus_json)
+    plan = json.loads(args.plan_json.read_text(encoding="utf-8"))
+    from transformers import AutoTokenizer
+
+    tokenizer = AutoTokenizer.from_pretrained(
+        "openai-community/gpt2",
+        revision="607a30d783dfa663caf39e06633721c8d4cfcd7e",
+        use_fast=True,
+        padding_side="left",
+    )
+    report = build_coverage_hole_report(corpus, tokenizer, plan)
+    args.json.parent.mkdir(parents=True, exist_ok=True)
+    args.json.write_text(
+        json.dumps(report, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+    )
+    sys.stdout.write(f"artifact_hash={report['artifact_hash']}\n")
+    sys.stdout.write(f"row_count={len(report['rows'])}\n")
+    sys.stdout.write(
+        f"uncovered_lexical_totals={report['watermarked_uncovered_lexical_totals']}\n"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/fuckmark/experiments/effectiveness_plan.py b/fuckmark/experiments/effectiveness_plan.py
index 7fc10183..bf42eb98 100644
--- a/fuckmark/experiments/effectiveness_plan.py
+++ b/fuckmark/experiments/effectiveness_plan.py
@@ -14,9 +14,17 @@
     ScheduleGeometryMode,
     SchedulePolicy,
     build_candidate_tokenizer_geometry,
+    content_region_combined_transform_registry,
+    content_region_coverage_transform_registry,
+    content_region_general_only_transform_registry,
+    key_blind_coverage_completion_transform_registry,
     key_blind_high_coverage_transform_registry,
     validate_effectiveness_profile_registry,
     validate_hard_invariants,
+    CONTENT_REGION_COMBINED_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_PROFILE_ID,
+    CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+    KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
 )
 
 
@@ -151,6 +159,18 @@ def _schedule_seed(
     return seed
 
 
+def _registry_for_profile(profile: EffectivenessTransformProfile):
+    if profile.profile_id == KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID:
+        return key_blind_coverage_completion_transform_registry()
+    if profile.profile_id == CONTENT_REGION_COVERAGE_PROFILE_ID:
+        return content_region_coverage_transform_registry()
+    if profile.profile_id == CONTENT_REGION_GENERAL_ONLY_PROFILE_ID:
+        return content_region_general_only_transform_registry()
+    if profile.profile_id == CONTENT_REGION_COMBINED_PROFILE_ID:
+        return content_region_combined_transform_registry()
+    return key_blind_high_coverage_transform_registry()
+
+
 def build_key_blind_high_coverage_plan(
     corpus: Any,
     tokenizer: Any,
@@ -159,7 +179,7 @@ def build_key_blind_high_coverage_plan(
     source_code_commit: str,
 ) -> dict[str, object]:
     _require_git_object_id("source_code_commit", source_code_commit)
-    registry = key_blind_high_coverage_transform_registry()
+    registry = _registry_for_profile(profile)
     validate_effectiveness_profile_registry(profile, registry)
     policy = SchedulePolicy(profile.schedule_policy_id)
     if policy is not SchedulePolicy.COVERAGE_GREEDY_KEY_BLIND:
diff --git a/fuckmark/experiments/measurement_threshold.py b/fuckmark/experiments/measurement_threshold.py
new file mode 100644
index 00000000..8231a49a
--- /dev/null
+++ b/fuckmark/experiments/measurement_threshold.py
@@ -0,0 +1,97 @@
+from __future__ import annotations
+
+import math
+
+from ..detectors import CalibrationScope, ComparisonOperator, calibrate_detector
+from ..detectors.calibration_statistics import exact_binomial_interval
+from ..hashing import sha256_json
+from ..tiny_dev_transform_hf import (
+    TEXT_ONLY_CALIBRATION_POPULATION_ID,
+    TEXT_ONLY_LENGTH_POLICY_ID,
+    TEXT_ONLY_PROMPT_BOUNDARY_MODE,
+    TEXT_ONLY_TOKEN_TRACK,
+    _text_only_weighted_evidence,
+)
+
+
+MEASUREMENT_STABILITY_VERSION = "open-detector-measurement-stability-v1"
+MEASUREMENT_STABILITY_TARGET_FPR = 0.01
+MEASUREMENT_STABILITY_COMPARISON = ">="
+
+
+def build_fixed_threshold_artifact(
+    calibration_corpus,
+    adapter,
+    *,
+    frozen_at_utc: str,
+) -> dict[str, object]:
+    negatives = calibration_corpus.calibration_samples()
+    audit = calibration_corpus.audit_samples()
+    evidence = tuple(_text_only_weighted_evidence(sample, adapter) for sample in negatives)
+    audit_evidence = tuple(_text_only_weighted_evidence(sample, adapter) for sample in audit)
+    scope = CalibrationScope.create(
+        corpus_id=calibration_corpus.manifest.corpus_id,
+        population_id=TEXT_ONLY_CALIBRATION_POPULATION_ID,
+        length_policy_id=TEXT_ONLY_LENGTH_POLICY_ID,
+        token_track=TEXT_ONLY_TOKEN_TRACK,
+        prompt_boundary_mode=TEXT_ONLY_PROMPT_BOUNDARY_MODE,
+    )
+    bundle = calibrate_detector(
+        evidence,
+        scope,
+        target_fprs=(0.05, 0.01),
+        comparison_operator=ComparisonOperator.GREATER_THAN_OR_EQUAL,
+        confidence_level=0.95,
+    )
+    scores = sorted(value.raw_score for value in evidence)
+    count = len(scores)
+    order_statistic = count - math.floor(MEASUREMENT_STABILITY_TARGET_FPR * count) + 1
+    threshold = scores[order_statistic - 1]
+    calibration_exceedances = sum(1 for value in scores if value >= threshold)
+    audit_scores = tuple(value.raw_score for value in audit_evidence)
+    audit_exceedances = sum(1 for value in audit_scores if value >= threshold)
+    interval = exact_binomial_interval(audit_exceedances, len(audit_scores))
+    payload = {
+        "algorithm_version": MEASUREMENT_STABILITY_VERSION,
+        "frozen_at_utc": frozen_at_utc,
+        "detector_identity_hash": bundle.detector_identity.identity_hash,
+        "calibration_bundle_hash": bundle.bundle_hash,
+        "calibration_corpus_artifact_hash": calibration_corpus.artifact_hash,
+        "calibration_negative_count": count,
+        "audit_negative_count": len(audit_scores),
+        "target_fpr": MEASUREMENT_STABILITY_TARGET_FPR,
+        "comparison_operator": MEASUREMENT_STABILITY_COMPARISON,
+        "threshold_definition": (
+            "ascending order statistic n - floor(target_fpr * n) + 1 of the calibration "
+            "negative weighted-mean scores (the 1015th of 1024 for target FPR 0.01, bounding "
+            "calibration exceedances at floor(target_fpr * n)); detection when score >= "
+            "threshold; float64 scores as computed; no tie rounding"
+        ),
+        "threshold_order_statistic": order_statistic,
+        "threshold": threshold,
+        "calibration_exceedances": calibration_exceedances,
+        "audit_exceedances": audit_exceedances,
+        "audit_realized_fpr": audit_exceedances / len(audit_scores),
+        "audit_fpr_confidence_interval_95": [interval.lower, interval.upper],
+    }
+    return {**payload, "artifact_hash": sha256_json(payload)}
+
+
+def validate_fixed_threshold_artifact(artifact, detector_identity_hash: str) -> float:
+    if not isinstance(artifact, dict):
+        raise TypeError("fixed threshold artifact must be a mapping")
+    if artifact.get("algorithm_version") != MEASUREMENT_STABILITY_VERSION:
+        raise ValueError("unsupported fixed threshold artifact version")
+    if artifact.get("detector_identity_hash") != detector_identity_hash:
+        raise ValueError("fixed threshold detector identity does not match the scoring detector")
+    if artifact.get("comparison_operator") != MEASUREMENT_STABILITY_COMPARISON:
+        raise ValueError("fixed threshold comparison operator does not match the scoring rule")
+    if artifact.get("target_fpr") != MEASUREMENT_STABILITY_TARGET_FPR:
+        raise ValueError("fixed threshold target FPR does not match the scoring target")
+    expected = sha256_json({key: value for key, value in artifact.items() if key != "artifact_hash"})
+    if artifact.get("artifact_hash") != expected:
+        raise ValueError("fixed threshold artifact hash does not replay")
+    threshold = artifact.get("threshold")
+    if not isinstance(threshold, float) or not 0.0 <= threshold <= 1.0:
+        raise ValueError("fixed threshold must be a probability float")
+    return threshold
diff --git a/fuckmark/tiny_dev_budget_scaled_robustness.py b/fuckmark/tiny_dev_budget_scaled_robustness.py
new file mode 100644
index 00000000..1e8f19cc
--- /dev/null
+++ b/fuckmark/tiny_dev_budget_scaled_robustness.py
@@ -0,0 +1,208 @@
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+import unicodedata
+from pathlib import Path
+
+from .corpus import load_tiny_dev_corpus_by_version_json
+from .experiments.mid_dev_quality import protected_span_violation_count, word_edit_rate
+from .hashing import sha256_json, sha256_text
+from .transforms import validate_hard_invariants, InvariantStatus
+
+
+BUDGET_SCALED_ROBUSTNESS_VERSION = "budget-scaled-robustness-v1"
+FORBIDDEN_CATEGORIES = ("Cc", "Cf", "Mn", "Mc", "Me", "Zl", "Zp")
+WORD_EDIT_RATE_MAX = 0.30
+
+
+def _forbidden_codepoints(text: str) -> tuple[str, ...]:
+    return tuple(
+        f"U+{ord(character):04X}({unicodedata.category(character)})"
+        for character in sorted(set(text))
+        if unicodedata.category(character) in FORBIDDEN_CATEGORIES
+        or (unicodedata.category(character) == "Zs" and character != " ")
+    )
+
+
+def _introduced_forbidden_codepoints(source_text: str, transformed_text: str) -> tuple[str, ...]:
+    source_alphabet = set(source_text)
+    return tuple(
+        f"U+{ord(character):04X}({unicodedata.category(character)})"
+        for character in sorted(set(transformed_text) - source_alphabet)
+        if unicodedata.category(character) in FORBIDDEN_CATEGORIES
+        or (unicodedata.category(character) == "Zs" and character != " ")
+    )
+
+
+def _introduced_non_ascii(source_text: str, transformed_text: str) -> tuple[str, ...]:
+    source_alphabet = set(source_text)
+    return tuple(
+        f"U+{ord(character):04X}"
+        for character in sorted(set(transformed_text) - source_alphabet)
+        if not character.isascii()
+    )
+
+
+def _cf_stripped(text: str) -> str:
+    return "".join(
+        character
+        for character in text
+        if unicodedata.category(character) != "Cf"
+    )
+
+
+def _robustness_row(source_text: str, transformed_text: str) -> dict[str, object]:
+    normalization_noops = {
+        "nfc": unicodedata.normalize("NFC", transformed_text) == transformed_text,
+        "nfd": unicodedata.normalize("NFD", transformed_text) == transformed_text,
+        "nfkc": unicodedata.normalize("NFKC", transformed_text) == transformed_text,
+        "nfkd": unicodedata.normalize("NFKD", transformed_text) == transformed_text,
+    }
+    source_normalization_noops = {
+        "nfc": unicodedata.normalize("NFC", source_text) == source_text,
+        "nfd": unicodedata.normalize("NFD", source_text) == source_text,
+        "nfkc": unicodedata.normalize("NFKC", source_text) == source_text,
+        "nfkd": unicodedata.normalize("NFKD", source_text) == source_text,
+    }
+    introduced_instability = tuple(
+        form
+        for form in normalization_noops
+        if source_normalization_noops[form] and not normalization_noops[form]
+    )
+    invariant_status = validate_hard_invariants(source_text, transformed_text).status
+    row = {
+        "source_text_hash": sha256_text(source_text),
+        "transformed_text_hash": sha256_text(transformed_text),
+        "transformed_is_ascii": transformed_text.isascii(),
+        "preexisting_forbidden_codepoints": _forbidden_codepoints(transformed_text),
+        "introduced_forbidden_codepoints": _introduced_forbidden_codepoints(source_text, transformed_text),
+        "introduced_non_ascii_codepoints": _introduced_non_ascii(source_text, transformed_text),
+        "normalization_noops": normalization_noops,
+        "source_normalization_noops": source_normalization_noops,
+        "introduced_normalization_instability": introduced_instability,
+        "cf_strip_noop": _cf_stripped(transformed_text) == transformed_text,
+        "word_edit_rate": word_edit_rate(source_text, transformed_text),
+        "protected_span_violation_count": protected_span_violation_count(source_text, transformed_text),
+        "hard_invariant_status": invariant_status.value,
+    }
+    gates_pass = (
+        not row["introduced_forbidden_codepoints"]
+        and not row["introduced_non_ascii_codepoints"]
+        and not row["introduced_normalization_instability"]
+        and row["cf_strip_noop"]
+        and row["word_edit_rate"] <= WORD_EDIT_RATE_MAX
+        and row["protected_span_violation_count"] == 0
+        and invariant_status is InvariantStatus.PASS
+    )
+    return {**row, "gates_pass": gates_pass}
+
+
+def build_budget_scaled_robustness_report(
+    corpora: tuple[object, ...],
+    plans: tuple[dict[str, object], ...],
+) -> dict[str, object]:
+    corpus_by_artifact: dict[str, object] = {}
+    for corpus in corpora:
+        corpus_by_artifact[corpus.artifact_hash] = corpus
+    corpus_text_hashes: list[set[str]] = [
+        {sample.text_sha256 for sample in corpus.manifest.samples} for corpus in corpora
+    ]
+    pairwise_overlaps = {}
+    for left in range(len(corpora)):
+        for right in range(left + 1, len(corpora)):
+            pairwise_overlaps[f"{left}-{right}"] = len(
+                corpus_text_hashes[left] & corpus_text_hashes[right]
+            )
+    rows: list[dict[str, object]] = []
+    for plan in plans:
+        corpus = corpus_by_artifact.get(plan["tiny_dev_artifact_hash"])
+        if corpus is None:
+            raise ValueError("robustness report received a plan whose corpus was not supplied")
+        sources = {sample.sample_id: sample for sample in corpus.manifest.samples}
+        for variant in plan["variants"]:
+            sample = sources[variant["source_sample_id"]]
+            rows.append(
+                {
+                    "plan_hash": plan["plan_hash"],
+                    "corpus_artifact_hash": corpus.artifact_hash,
+                    "source_sample_id": variant["source_sample_id"],
+                    "requested_budget": variant["requested_budget"],
+                    **_robustness_row(sample.text, variant["transformed_text"]),
+                }
+            )
+    row_tuple = tuple(rows)
+    summary = {
+        "row_count": len(row_tuple),
+        "gate_pass_fraction": sum(1 for row in row_tuple if row["gates_pass"]) / len(row_tuple) if row_tuple else 1.0,
+        "all_introduced_codepoints_clean": all(
+            not row["introduced_forbidden_codepoints"] and not row["introduced_non_ascii_codepoints"]
+            for row in row_tuple
+        ),
+        "all_normalization_stability_preserved": all(
+            not row["introduced_normalization_instability"] for row in row_tuple
+        ),
+        "rows_with_preexisting_normalization_instability": sum(
+            1
+            for row in row_tuple
+            if not all(row["normalization_noops"].values())
+        ),
+        "all_cf_strip_noop": all(row["cf_strip_noop"] for row in row_tuple),
+        "max_word_edit_rate": max((row["word_edit_rate"] for row in row_tuple), default=0.0),
+        "total_protected_span_violations": sum(
+            row["protected_span_violation_count"] for row in row_tuple
+        ),
+        "all_hard_invariants_pass": all(
+            row["hard_invariant_status"] == InvariantStatus.PASS.value for row in row_tuple
+        ),
+        "corpus_pairwise_text_hash_overlaps": pairwise_overlaps,
+    }
+    payload = {
+        "algorithm_version": BUDGET_SCALED_ROBUSTNESS_VERSION,
+        "word_edit_rate_max": WORD_EDIT_RATE_MAX,
+        "forbidden_categories": FORBIDDEN_CATEGORIES,
+        "corpus_artifact_hashes": tuple(corpus.artifact_hash for corpus in corpora),
+        "plan_hashes": tuple(plan["plan_hash"] for plan in plans),
+        "rows": row_tuple,
+        "summary": summary,
+    }
+    return {**payload, "artifact_hash": sha256_json(payload)}
+
+
+def _load_plan(path: Path) -> dict[str, object]:
+    value = json.loads(path.read_text(encoding="utf-8"))
+    if not isinstance(value, dict):
+        raise ValueError("expected a JSON object")
+    return value
+
+
+def _parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(prog="fuckmark-tiny-dev-budget-scaled-robustness")
+    parser.add_argument("--corpus-json", type=Path, action="append", required=True)
+    parser.add_argument("--plan-json", type=Path, action="append", required=True)
+    parser.add_argument("--json", type=Path, required=True)
+    return parser
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = _parser().parse_args(argv)
+    corpora = tuple(
+        load_tiny_dev_corpus_by_version_json(path) for path in args.corpus_json
+    )
+    plans = tuple(_load_plan(path) for path in args.plan_json)
+    report = build_budget_scaled_robustness_report(corpora, plans)
+    args.json.parent.mkdir(parents=True, exist_ok=True)
+    args.json.write_text(
+        json.dumps(report, indent=2, sort_keys=True, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+    sys.stdout.write(f"artifact_hash={report['artifact_hash']}\n")
+    sys.stdout.write(f"row_count={report['summary']['row_count']}\n")
+    sys.stdout.write(f"gate_pass_fraction={report['summary']['gate_pass_fraction']}\n")
+    sys.stdout.write(f"json={args.json.as_posix()}\n")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/fuckmark/tiny_dev_corpus_hf.py b/fuckmark/tiny_dev_corpus_hf.py
index f37b5f82..8a1c001e 100644
--- a/fuckmark/tiny_dev_corpus_hf.py
+++ b/fuckmark/tiny_dev_corpus_hf.py
@@ -11,6 +11,9 @@
     ModelTokenizerIdentity,
     PaddingSide,
     WatermarkCondition,
+    build_real_tiny_dev_v3_corpus,
+    load_tiny_dev_corpus_json,
+    load_tiny_dev_v3_corpus_json,
 )
 from .corpus.tiny_dev import TINY_DEV_TARGET_LENGTH
 from .corpus.tiny_dev_generation import (
@@ -215,12 +218,26 @@ def _parser() -> argparse.ArgumentParser:
     parser.add_argument("--temperature", type=float, default=0.8)
     parser.add_argument("--top-k", type=int, default=50)
     parser.add_argument("--top-p", type=float, default=0.95)
+    parser.add_argument(
+        "--profile",
+        choices=("v2", "v3"),
+        default="v2",
+    )
+    parser.add_argument(
+        "--attack-pairs-per-domain",
+        type=int,
+        default=1,
+    )
     parser.add_argument("--json", type=Path, default=Path("artifacts/tiny-dev-corpus.json"))
     return parser
 
 
 def main(argv: list[str] | None = None) -> int:
     args = _parser().parse_args(argv)
+    if args.profile == "v3" and args.attack_pairs_per_domain < 1:
+        raise ValueError("the v3 profile requires at least one attack pair per domain")
+    if args.profile == "v2" and args.attack_pairs_per_domain != 1:
+        raise ValueError("the v2 profile is frozen at one attack pair per domain")
     backend = HuggingFaceTinyDevBackend(
         args.model,
         args.model_revision,
@@ -229,13 +246,28 @@ def main(argv: list[str] | None = None) -> int:
         top_k=args.top_k,
         top_p=args.top_p,
     )
-    artifact = build_real_tiny_dev_corpus(
-        backend,
-        seed_base=args.seed_base,
-        max_attempts=args.max_attempts,
-    )
+    if args.profile == "v3":
+        artifact = build_real_tiny_dev_v3_corpus(
+            backend,
+            seed_base=args.seed_base,
+            attack_pairs_per_domain=args.attack_pairs_per_domain,
+            max_attempts=args.max_attempts,
+        )
+    else:
+        artifact = build_real_tiny_dev_corpus(
+            backend,
+            seed_base=args.seed_base,
+            max_attempts=args.max_attempts,
+        )
     args.json.parent.mkdir(parents=True, exist_ok=True)
     args.json.write_text(canonical_json_text(artifact) + "\n", encoding="utf-8")
+    loaded = (
+        load_tiny_dev_v3_corpus_json(args.json)
+        if args.profile == "v3"
+        else load_tiny_dev_corpus_json(args.json)
+    )
+    if loaded.artifact_hash != artifact.artifact_hash:
+        raise RuntimeError("canonical corpus JSON did not replay the generated artifact hash")
     sys.stdout.write(f"artifact_hash={artifact.artifact_hash}\n")
     sys.stdout.write(f"manifest_hash={artifact.manifest.manifest_hash}\n")
     sys.stdout.write(f"prompt_count={len(artifact.manifest.prompts)}\n")
@@ -245,6 +277,9 @@ def main(argv: list[str] | None = None) -> int:
         f"generation_signature_hash={artifact.generation_matching_signature_hash}\n"
     )
     sys.stdout.write(f"watermark_condition_hash={artifact.watermark_condition_hash}\n")
+    sys.stdout.write(f"profile={args.profile}\n")
+    if args.profile == "v3":
+        sys.stdout.write(f"attack_pairs_per_domain={args.attack_pairs_per_domain}\n")
     sys.stdout.write(f"json={args.json.as_posix()}\n")
     return 0
 
diff --git a/fuckmark/tiny_dev_effectiveness_plan_hf.py b/fuckmark/tiny_dev_effectiveness_plan_hf.py
index ca3cbd56..e524c806 100644
--- a/fuckmark/tiny_dev_effectiveness_plan_hf.py
+++ b/fuckmark/tiny_dev_effectiveness_plan_hf.py
@@ -6,7 +6,7 @@
 from datetime import datetime, timezone
 from pathlib import Path
 
-from .corpus import load_tiny_dev_corpus_json
+from .corpus import load_tiny_dev_corpus_by_version_json
 from .durable_io import write_canonical_json_fsynced
 from .experiments.effectiveness_plan import (
     build_key_blind_high_coverage_plan,
@@ -17,7 +17,15 @@
     DEFAULT_MODEL_REVISION,
     runtime_tokenizer_identity_public,
 )
-from .transforms import KEY_BLIND_HIGH_COVERAGE_PROFILE
+from .transforms import (
+    KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+    KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+    KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+    CONTENT_REGION_COMBINED_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_PROFILE_ID,
+    CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+    resolve_effectiveness_profile,
+)
 
 
 EFFECTIVENESS_PLAN_PROVENANCE_VERSION = "effectiveness-plan-provenance-v1"
@@ -53,12 +61,43 @@ def _provenance(
     return {**payload, "provenance_hash": sha256_json(payload)}
 
 
+def _parse_budgets(raw: str) -> tuple[int, ...]:
+    if not raw:
+        return ()
+    values: list[int] = []
+    for chunk in raw.split(","):
+        stripped = chunk.strip()
+        if not stripped:
+            raise ValueError("budget list contains an empty entry")
+        value = int(stripped)
+        if value <= 0:
+            raise ValueError("budgets must be positive integers")
+        values.append(value)
+    budgets = tuple(sorted(set(values)))
+    if budgets != tuple(values):
+        raise ValueError("budgets must be provided in ascending order without duplicates")
+    return budgets
+
+
 def _parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser(prog="fuckmark-tiny-dev-effectiveness-plan-hf")
     parser.add_argument("--corpus-json", type=Path, required=True)
     parser.add_argument("--model", default=DEFAULT_MODEL_ID)
     parser.add_argument("--model-revision", default=DEFAULT_MODEL_REVISION)
     parser.add_argument("--source-code-commit", required=True)
+    parser.add_argument(
+        "--profile-id",
+        default=KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+        choices=(
+            KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+            KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+            KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+            CONTENT_REGION_COVERAGE_PROFILE_ID,
+            CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+            CONTENT_REGION_COMBINED_PROFILE_ID,
+        ),
+    )
+    parser.add_argument("--budgets", default="")
     parser.add_argument(
         "--plan-json",
         type=Path,
@@ -79,7 +118,8 @@ def main(argv: list[str] | None = None) -> int:
     except ImportError as error:
         raise RuntimeError("Install the pinned TinyDev Transformers dependencies first") from error
 
-    corpus = load_tiny_dev_corpus_json(args.corpus_json)
+    profile = resolve_effectiveness_profile(args.profile_id, _parse_budgets(args.budgets))
+    corpus = load_tiny_dev_corpus_by_version_json(args.corpus_json)
     tokenizer = AutoTokenizer.from_pretrained(
         args.model,
         revision=args.model_revision,
@@ -96,7 +136,7 @@ def main(argv: list[str] | None = None) -> int:
     plan = build_key_blind_high_coverage_plan(
         corpus,
         tokenizer,
-        profile=KEY_BLIND_HIGH_COVERAGE_PROFILE,
+        profile=profile,
         source_code_commit=args.source_code_commit,
     )
     write_canonical_json_fsynced(args.plan_json, plan)
@@ -104,14 +144,14 @@ def main(argv: list[str] | None = None) -> int:
     provenance = _provenance(
         source_code_commit=args.source_code_commit,
         plan_hash=plan["plan_hash"],
-        profile_hash=KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_hash,
+        profile_hash=profile.profile_hash,
         plan_started_at=started_at,
         plan_fsynced_at=fsynced_at,
     )
     write_canonical_json_fsynced(args.provenance_json, provenance)
 
-    sys.stdout.write(f"profile_id={KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_id}\n")
-    sys.stdout.write(f"profile_hash={KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_hash}\n")
+    sys.stdout.write(f"profile_id={profile.profile_id}\n")
+    sys.stdout.write(f"profile_hash={profile.profile_hash}\n")
     sys.stdout.write(f"plan_hash={plan['plan_hash']}\n")
     sys.stdout.write(f"variant_count={len(plan['variants'])}\n")
     sys.stdout.write(f"plan_json={args.plan_json.as_posix()}\n")
diff --git a/fuckmark/tiny_dev_effectiveness_score_hf.py b/fuckmark/tiny_dev_effectiveness_score_hf.py
index 1ac2f5b6..29f1241d 100644
--- a/fuckmark/tiny_dev_effectiveness_score_hf.py
+++ b/fuckmark/tiny_dev_effectiveness_score_hf.py
@@ -10,7 +10,7 @@
 from typing import Any
 
 from .adapters import HuggingFaceSynthIDAdapter, HuggingFaceSynthIDConfig
-from .corpus import load_tiny_dev_corpus_json
+from .corpus import load_tiny_dev_corpus_by_version_json
 from .detectors import weighted_mean_evidence
 from .durable_io import write_canonical_json_fsynced
 from .experiments.effectiveness_plan import validate_key_blind_high_coverage_plan
@@ -31,7 +31,17 @@
     _threshold,
     _word_edit_distance,
 )
-from .transforms import KEY_BLIND_HIGH_COVERAGE_PROFILE
+from .transforms import (
+    CONTENT_REGION_COMBINED_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_PROFILE_ID,
+    CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+    KEY_BLIND_HIGH_COVERAGE_PROFILE,
+    KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+    KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+    KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+    EffectivenessTransformProfile,
+    resolve_effectiveness_profile,
+)
 
 
 KEY_BLIND_HIGH_COVERAGE_EVIDENCE_VERSION = "key-blind-high-coverage-evidence-v1"
@@ -87,12 +97,33 @@ def score_key_blind_high_coverage_plan(
     tokenizer: Any,
     plan: Mapping[str, object],
     adapter: HuggingFaceSynthIDAdapter,
+    *,
+    profile: EffectivenessTransformProfile | None = None,
+    fixed_threshold: Mapping[str, object] | None = None,
 ) -> dict[str, object]:
-    validate_key_blind_high_coverage_plan(plan, corpus, KEY_BLIND_HIGH_COVERAGE_PROFILE)
-    if adapter.ngram_len != KEY_BLIND_HIGH_COVERAGE_PROFILE.ngram_len:
+    active_profile = profile if profile is not None else KEY_BLIND_HIGH_COVERAGE_PROFILE
+    validate_key_blind_high_coverage_plan(plan, corpus, active_profile)
+    if adapter.ngram_len != active_profile.ngram_len:
         raise ValueError("detector ngram length does not match the frozen effectiveness profile")
     calibration = _text_only_calibration(corpus, adapter)
-    threshold = _threshold(calibration, PRIMARY_TARGET_FPR)
+    if fixed_threshold is not None:
+        from .experiments.measurement_threshold import validate_fixed_threshold_artifact
+
+        threshold_value = validate_fixed_threshold_artifact(
+            dict(fixed_threshold),
+            calibration.detector_identity.identity_hash,
+        )
+        threshold_source = "open-detector-measurement-stability-v1"
+        fixed_threshold_artifact_hash = fixed_threshold["artifact_hash"]
+        threshold_hash_for_payload = fixed_threshold["artifact_hash"]
+        threshold_target_fpr = fixed_threshold["target_fpr"]
+    else:
+        threshold = _threshold(calibration, PRIMARY_TARGET_FPR)
+        threshold_value = threshold.value
+        threshold_source = "per-corpus-calibration"
+        fixed_threshold_artifact_hash = None
+        threshold_hash_for_payload = threshold.threshold_hash
+        threshold_target_fpr = threshold.target_fpr
     sources = {sample.sample_id: sample for sample in _attack_samples(corpus)}
     pristine = {
         sample_id: _text_only_weighted_evidence(sample, adapter)
@@ -132,8 +163,8 @@ def score_key_blind_high_coverage_plan(
             "pristine_score": original.raw_score,
             "transformed_score": transformed.raw_score,
             "score_drop": original.raw_score - transformed.raw_score,
-            "pristine_detected": original.raw_score >= threshold.value,
-            "transformed_detected": transformed.raw_score >= threshold.value,
+            "pristine_detected": original.raw_score >= threshold_value,
+            "transformed_detected": transformed.raw_score >= threshold_value,
         }
         rows.append({**row, "row_hash": sha256_json(row)})
     row_tuple = tuple(rows)
@@ -146,14 +177,16 @@ def score_key_blind_high_coverage_plan(
         "tiny_dev_artifact_hash": corpus.artifact_hash,
         "corpus_manifest_hash": corpus.manifest.manifest_hash,
         "plan_hash": plan["plan_hash"],
-        "profile_id": KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_id,
-        "profile_hash": KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_hash,
-        "ruleset_hash": KEY_BLIND_HIGH_COVERAGE_PROFILE.ruleset_hash,
+        "profile_id": active_profile.profile_id,
+        "profile_hash": active_profile.profile_hash,
+        "ruleset_hash": active_profile.ruleset_hash,
         "detector_identity_hash": calibration.detector_identity.identity_hash,
         "calibration_bundle_hash": calibration.bundle_hash,
-        "threshold_hash": threshold.threshold_hash,
-        "threshold_target_fpr": threshold.target_fpr,
-        "threshold_value": threshold.value,
+        "threshold_hash": threshold_hash_for_payload,
+        "threshold_target_fpr": threshold_target_fpr,
+        "threshold_value": threshold_value,
+        "threshold_source": threshold_source,
+        "fixed_threshold_artifact_hash": fixed_threshold_artifact_hash,
         "selection_detector_access_observed": plan["detector_access_observed"],
         "selection_secret_access_observed": plan["secret_access_observed"],
         "rows": row_tuple,
@@ -188,6 +221,24 @@ def _provenance(
     return {**payload, "provenance_hash": sha256_json(payload)}
 
 
+def _parse_budgets(raw: str) -> tuple[int, ...]:
+    if not raw:
+        return ()
+    values: list[int] = []
+    for chunk in raw.split(","):
+        stripped = chunk.strip()
+        if not stripped:
+            raise ValueError("budget list contains an empty entry")
+        value = int(stripped)
+        if value <= 0:
+            raise ValueError("budgets must be positive integers")
+        values.append(value)
+    budgets = tuple(sorted(set(values)))
+    if budgets != tuple(values):
+        raise ValueError("budgets must be provided in ascending order without duplicates")
+    return budgets
+
+
 def _parser() -> argparse.ArgumentParser:
     parser = argparse.ArgumentParser(prog="fuckmark-tiny-dev-effectiveness-score-hf")
     parser.add_argument("--corpus-json", type=Path, required=True)
@@ -196,6 +247,24 @@ def _parser() -> argparse.ArgumentParser:
     parser.add_argument("--model-revision", default=DEFAULT_MODEL_REVISION)
     parser.add_argument("--device", choices=("cpu", "cuda"), default="cpu")
     parser.add_argument("--source-code-commit", required=True)
+    parser.add_argument(
+        "--profile-id",
+        default=KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+        choices=(
+            KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+            KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+            KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+            CONTENT_REGION_COVERAGE_PROFILE_ID,
+            CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+            CONTENT_REGION_COMBINED_PROFILE_ID,
+        ),
+    )
+    parser.add_argument("--budgets", default="")
+    parser.add_argument(
+        "--fixed-threshold-json",
+        type=Path,
+        default=None,
+    )
     parser.add_argument(
         "--json",
         type=Path,
@@ -216,9 +285,10 @@ def main(argv: list[str] | None = None) -> int:
     except ImportError as error:
         raise RuntimeError("Install the pinned TinyDev Transformers dependencies first") from error
 
-    corpus = load_tiny_dev_corpus_json(args.corpus_json)
+    profile = resolve_effectiveness_profile(args.profile_id, _parse_budgets(args.budgets))
+    corpus = load_tiny_dev_corpus_by_version_json(args.corpus_json)
     plan = _load_json(args.plan_json)
-    validate_key_blind_high_coverage_plan(plan, corpus, KEY_BLIND_HIGH_COVERAGE_PROFILE)
+    validate_key_blind_high_coverage_plan(plan, corpus, profile)
     if plan["source_code_commit"] != args.source_code_commit:
         raise ValueError("score invocation commit does not match the frozen plan")
     tokenizer = AutoTokenizer.from_pretrained(
@@ -247,7 +317,17 @@ def main(argv: list[str] | None = None) -> int:
         device=args.device,
     )
     started_at = _now()
-    evidence = score_key_blind_high_coverage_plan(corpus, tokenizer, plan, adapter)
+    fixed_threshold = None
+    if args.fixed_threshold_json is not None:
+        fixed_threshold = _load_json(args.fixed_threshold_json)
+    evidence = score_key_blind_high_coverage_plan(
+        corpus,
+        tokenizer,
+        plan,
+        adapter,
+        profile=profile,
+        fixed_threshold=fixed_threshold,
+    )
     write_canonical_json_fsynced(args.json, evidence)
     fsynced_at = _now()
     provenance = _provenance(
@@ -259,7 +339,7 @@ def main(argv: list[str] | None = None) -> int:
     )
     write_canonical_json_fsynced(args.provenance_json, provenance)
 
-    sys.stdout.write(f"profile_id={KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_id}\n")
+    sys.stdout.write(f"profile_id={profile.profile_id}\n")
     sys.stdout.write(f"plan_hash={plan['plan_hash']}\n")
     sys.stdout.write(f"artifact_hash={evidence['artifact_hash']}\n")
     for summary in evidence["summaries"]:
diff --git a/fuckmark/tiny_dev_measurement_calibration_hf.py b/fuckmark/tiny_dev_measurement_calibration_hf.py
new file mode 100644
index 00000000..673db01a
--- /dev/null
+++ b/fuckmark/tiny_dev_measurement_calibration_hf.py
@@ -0,0 +1,220 @@
+from __future__ import annotations
+
+import argparse
+import sys
+from pathlib import Path
+
+from .config import canonical_json_text
+from .corpus import WatermarkLabel
+from .corpus.measurement_calibration import (
+    MEASUREMENT_CALIBRATION_PROMPT_SOURCE_ID,
+    MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT,
+    MEASUREMENT_CALIBRATION_SAMPLE_COUNT,
+    MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN,
+    build_measurement_calibration_corpus,
+    measurement_calibration_topics,
+)
+from .corpus.prompt import PromptRecord
+from .corpus.sample import CorpusSample
+from .corpus.schema import CorpusSplit, MAX_GENERATION_SEED
+from .corpus.tokenization import GenerationTokenRecord, TextOnlyTokenRecord
+from .corpus.tiny_dev import TINY_DEV_TARGET_LENGTH
+from .corpus.tiny_dev_generation import (
+    TINY_DEV_PROMPT_LICENSE_ID,
+    TINY_DEV_PROMPT_PROVENANCE,
+    TINY_DEV_SEED_POLICY_ID,
+    TinyDevGenerationError,
+    _TINY_DEV_TEMPLATES,
+)
+from .hashing import sha256_json, sha256_text
+from .tiny_dev_corpus_hf import DEFAULT_MODEL_ID, DEFAULT_MODEL_REVISION, HuggingFaceTinyDevBackend
+
+
+MEASUREMENT_CALIBRATION_GENERATION_VERSION = "measurement-calibration-generation-v1"
+MEASUREMENT_CALIBRATION_SEED_STRIDE = 16
+MEASUREMENT_CALIBRATION_MAX_ATTEMPTS = 16
+MEASUREMENT_CALIBRATION_TOPIC_OFFSET = 100
+
+
+def build_measurement_calibration_prompt_records() -> tuple[PromptRecord, ...]:
+    topics = measurement_calibration_topics()
+    if len(topics) != MEASUREMENT_CALIBRATION_TOPICS_PER_DOMAIN:
+        raise ValueError("measurement calibration topic pool must contain 40 topics")
+    source_hash = sha256_json(
+        {
+            "algorithm_version": MEASUREMENT_CALIBRATION_GENERATION_VERSION,
+            "source_id": MEASUREMENT_CALIBRATION_PROMPT_SOURCE_ID,
+            "license_id": TINY_DEV_PROMPT_LICENSE_ID,
+            "provenance": TINY_DEV_PROMPT_PROVENANCE,
+            "topics": topics,
+            "templates": tuple(
+                (domain.value, _TINY_DEV_TEMPLATES[domain])
+                for domain in _TINY_DEV_TEMPLATES
+            ),
+        }
+    )
+    records: list[PromptRecord] = []
+    for domain in _TINY_DEV_TEMPLATES:
+        template = _TINY_DEV_TEMPLATES[domain]
+        for local_index, topic in enumerate(topics):
+            topic_index = MEASUREMENT_CALIBRATION_TOPIC_OFFSET + local_index
+            prompt_id = f"measurement-calibration-{domain.value}-{topic_index:02d}"
+            records.append(
+                PromptRecord.create(
+                    prompt_id=prompt_id,
+                    prompt_family_id=f"measurement-calibration-family-{domain.value}-{topic_index:02d}",
+                    domain=domain,
+                    split=CorpusSplit.THRESHOLD_CALIBRATION,
+                    source_id=MEASUREMENT_CALIBRATION_PROMPT_SOURCE_ID,
+                    source_hash=source_hash,
+                    license_id=TINY_DEV_PROMPT_LICENSE_ID,
+                    provenance=TINY_DEV_PROMPT_PROVENANCE,
+                    text=template.format(topic=topic),
+                )
+            )
+    return tuple(sorted(records, key=lambda value: value.prompt_id))
+
+
+def _build_slot_sample(
+    *,
+    prompt,
+    slot: int,
+    generated,
+    backend,
+    seed: int,
+) -> CorpusSample:
+    model = backend.model_identity
+    generation = backend.generation_parameters(seed)
+    if generation.seed != seed:
+        raise TinyDevGenerationError("backend generation parameters do not bind the requested seed")
+    if generation.seed_policy_id != TINY_DEV_SEED_POLICY_ID:
+        raise TinyDevGenerationError("backend seed policy does not match the frozen tiny development policy")
+    generation_tokens = GenerationTokenRecord.create(
+        input_token_ids=generated.input_token_ids,
+        attention_mask=generated.attention_mask,
+        generated_sequence_ids=generated.input_token_ids + generated.continuation_token_ids,
+        continuation_start_index=len(generated.input_token_ids),
+        continuation_token_ids=generated.continuation_token_ids,
+        prompt_length_after_templating=sum(generated.attention_mask),
+        model_tokenizer_identity_hash=model.identity_hash,
+    )
+    text_only = None
+    if generated.text_only_token_ids is not None:
+        text_only = TextOnlyTokenRecord.create(
+            source_text_sha256=sha256_text(generated.text),
+            token_ids=generated.text_only_token_ids,
+            model_tokenizer_identity_hash=model.identity_hash,
+        )
+    sample_id = f"{prompt.prompt_id}-s{slot:02d}-{WatermarkLabel.UNWATERMARKED.value}"
+    return CorpusSample.create(
+        sample_id=sample_id,
+        match_id=f"match-{sample_id}",
+        prompt_id=prompt.prompt_id,
+        prompt_family_id=prompt.prompt_family_id,
+        domain=prompt.domain,
+        split=prompt.split,
+        label=WatermarkLabel.UNWATERMARKED,
+        text=generated.text,
+        model=model,
+        generation=generation,
+        watermark=backend.watermark_condition,
+        target_length=TINY_DEV_TARGET_LENGTH,
+        generation_tokens=generation_tokens,
+        text_only_tokens=text_only,
+    )
+
+
+def build_real_measurement_calibration_corpus(
+    backend: HuggingFaceTinyDevBackend,
+    *,
+    corpus_id: str = "fuckmark-measurement-calibration-v1",
+    seed_base: int = 500000,
+) -> MeasurementCalibrationCorpus:
+    if type(seed_base) is not int or seed_base < 0:
+        raise ValueError("seed_base must be a non-negative integer")
+    prompts = build_measurement_calibration_prompt_records()
+    slot_count = len(prompts) * MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT
+    if seed_base + slot_count * MEASUREMENT_CALIBRATION_SEED_STRIDE + MEASUREMENT_CALIBRATION_MAX_ATTEMPTS > MAX_GENERATION_SEED:
+        raise ValueError("measurement calibration seed schedule exceeds the 64-bit range")
+
+    samples: list[object] = []
+    seen_text_hashes: set[str] = set()
+    seen_token_hashes: set[str] = set()
+    slot_index = 0
+    for prompt in prompts:
+        for slot in range(MEASUREMENT_CALIBRATION_SEEDS_PER_PROMPT):
+            slot_seed_base = seed_base + slot_index * MEASUREMENT_CALIBRATION_SEED_STRIDE
+            slot_index += 1
+            accepted = False
+            for attempt in range(MEASUREMENT_CALIBRATION_MAX_ATTEMPTS):
+                seed = slot_seed_base + attempt
+                try:
+                    generated = backend.generate(prompt.text, seed, watermarked=False)
+                except RuntimeError:
+                    continue
+                if len(generated.continuation_token_ids) != TINY_DEV_TARGET_LENGTH:
+                    continue
+                if not generated.text.strip():
+                    continue
+                text_hash = sha256_text(generated.text)
+                token_hash = sha256_json(generated.continuation_token_ids)
+                if text_hash in seen_text_hashes or token_hash in seen_token_hashes:
+                    continue
+                samples.append(
+                    _build_slot_sample(
+                        prompt=prompt,
+                        slot=slot,
+                        generated=generated,
+                        backend=backend,
+                        seed=seed,
+                    )
+                )
+                seen_text_hashes.add(text_hash)
+                seen_token_hashes.add(token_hash)
+                accepted = True
+                break
+            if not accepted:
+                raise RuntimeError(
+                    f"could not produce an exact unique 64-token negative for {prompt.prompt_id} slot {slot}"
+                )
+    if len(samples) != MEASUREMENT_CALIBRATION_SAMPLE_COUNT:
+        raise RuntimeError("measurement calibration sample count does not match the frozen profile")
+    return build_measurement_calibration_corpus(corpus_id, prompts, samples)
+
+
+def _parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(prog="fuckmark-tiny-dev-measurement-calibration-hf")
+    parser.add_argument("--model", default=DEFAULT_MODEL_ID)
+    parser.add_argument("--model-revision", default=DEFAULT_MODEL_REVISION)
+    parser.add_argument("--device", choices=("auto", "cpu", "cuda"), default="auto")
+    parser.add_argument("--seed-base", type=int, default=500000)
+    parser.add_argument("--temperature", type=float, default=0.8)
+    parser.add_argument("--top-k", type=int, default=50)
+    parser.add_argument("--top-p", type=float, default=0.95)
+    parser.add_argument("--json", type=Path, required=True)
+    return parser
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = _parser().parse_args(argv)
+    backend = HuggingFaceTinyDevBackend(
+        args.model,
+        args.model_revision,
+        device=args.device,
+        temperature=args.temperature,
+        top_k=args.top_k,
+        top_p=args.top_p,
+    )
+    artifact = build_real_measurement_calibration_corpus(backend, seed_base=args.seed_base)
+    args.json.parent.mkdir(parents=True, exist_ok=True)
+    args.json.write_text(canonical_json_text(artifact) + "\n", encoding="utf-8")
+    sys.stdout.write(f"artifact_hash={artifact.artifact_hash}\n")
+    sys.stdout.write(f"manifest_hash={artifact.manifest.manifest_hash}\n")
+    sys.stdout.write(f"sample_count={len(artifact.manifest.samples)}\n")
+    sys.stdout.write(f"model_identity_hash={artifact.model_identity_hash}\n")
+    sys.stdout.write(f"json={args.json.as_posix()}\n")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/fuckmark/tiny_dev_measurement_threshold_hf.py b/fuckmark/tiny_dev_measurement_threshold_hf.py
new file mode 100644
index 00000000..d7df93ca
--- /dev/null
+++ b/fuckmark/tiny_dev_measurement_threshold_hf.py
@@ -0,0 +1,73 @@
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from datetime import datetime, timezone
+from pathlib import Path
+
+from .adapters import HuggingFaceSynthIDAdapter, HuggingFaceSynthIDConfig
+from .corpus.measurement_calibration_io import load_measurement_calibration_corpus_json
+from .durable_io import write_canonical_json_fsynced
+from .experiments.measurement_threshold import build_fixed_threshold_artifact
+from .tiny_dev_context_survival_plan_hf import (
+    DEFAULT_MODEL_ID,
+    DEFAULT_MODEL_REVISION,
+    runtime_tokenizer_identity_public,
+)
+from .tiny_dev_detector_hf import default_watermark_payload
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(prog="fuckmark-tiny-dev-measurement-threshold-hf")
+    parser.add_argument("--calibration-corpus-json", type=Path, required=True)
+    parser.add_argument("--model", default=DEFAULT_MODEL_ID)
+    parser.add_argument("--model-revision", default=DEFAULT_MODEL_REVISION)
+    parser.add_argument("--device", choices=("cpu", "cuda"), default="cpu")
+    parser.add_argument("--json", type=Path, required=True)
+    args = parser.parse_args(argv)
+    try:
+        from transformers import AutoTokenizer
+    except ImportError as error:
+        raise RuntimeError("Install the pinned TinyDev Transformers dependencies first") from error
+
+    corpus = load_measurement_calibration_corpus_json(args.calibration_corpus_json)
+    tokenizer = AutoTokenizer.from_pretrained(
+        args.model,
+        revision=args.model_revision,
+        use_fast=True,
+        padding_side="left",
+    )
+    identity = runtime_tokenizer_identity_public(tokenizer, args.model, args.model_revision)
+    if identity.identity_hash != corpus.model_identity_hash:
+        raise RuntimeError("runtime tokenizer identity does not match the calibration corpus")
+    watermark_payload = default_watermark_payload()
+    adapter = HuggingFaceSynthIDAdapter.from_torch(
+        HuggingFaceSynthIDConfig(
+            ngram_len=watermark_payload["ngram_len"],
+            keys=watermark_payload["keys"],
+            context_history_size=watermark_payload["context_history_size"],
+            sampling_table_seed=watermark_payload["sampling_table_seed"],
+            sampling_table_size=watermark_payload["sampling_table_size"],
+            skip_first_ngram_calls=watermark_payload["skip_first_ngram_calls"],
+            debug_mode=watermark_payload["debug_mode"],
+        ),
+        device=args.device,
+    )
+    artifact = build_fixed_threshold_artifact(
+        corpus,
+        adapter,
+        frozen_at_utc=datetime.now(timezone.utc).isoformat(),
+    )
+    write_canonical_json_fsynced(args.json, artifact)
+    sys.stdout.write(f"artifact_hash={artifact['artifact_hash']}\n")
+    sys.stdout.write(f"threshold={artifact['threshold']!r}\n")
+    sys.stdout.write(f"calibration_exceedances={artifact['calibration_exceedances']}/{artifact['calibration_negative_count']}\n")
+    sys.stdout.write(f"audit_exceedances={artifact['audit_exceedances']}/{artifact['audit_negative_count']}\n")
+    sys.stdout.write(f"audit_realized_fpr={artifact['audit_realized_fpr']}\n")
+    sys.stdout.write(f"json={args.json.as_posix()}\n")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/fuckmark/transforms/__init__.py b/fuckmark/transforms/__init__.py
index cca9ca93..27f2fb99 100644
--- a/fuckmark/transforms/__init__.py
+++ b/fuckmark/transforms/__init__.py
@@ -1,12 +1,30 @@
 from .candidate_artifacts import CandidateConflict, CandidateEnumeration, CandidateRejection, TransformCandidate
 from .effectiveness_profile import (
+    CONTENT_REGION_COMBINED_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_SEED_BASE,
+    CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
     EFFECTIVENESS_PROFILE_ALGORITHM_VERSION,
+    KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+    KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE,
+    KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+    KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE,
     KEY_BLIND_HIGH_COVERAGE_BUDGETS,
     KEY_BLIND_HIGH_COVERAGE_PROFILE,
     KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
     KEY_BLIND_HIGH_COVERAGE_SEED_BASE,
     EffectivenessTransformProfile,
+    content_region_combined_profile,
+    content_region_combined_transform_registry,
+    content_region_coverage_profile,
+    content_region_coverage_transform_registry,
+    content_region_general_only_profile,
+    content_region_general_only_transform_registry,
+    key_blind_coverage_completion_profile,
+    key_blind_coverage_completion_transform_registry,
+    key_blind_full_pool_coverage_profile,
     key_blind_high_coverage_transform_registry,
+    resolve_effectiveness_profile,
     validate_effectiveness_profile_registry,
 )
 from .fidelity_readiness import (
@@ -196,6 +214,8 @@
     "HardInvariantSignature",
     "hard_invariant_signature",
     "key_blind_high_coverage_transform_registry",
+    "key_blind_full_pool_coverage_profile",
+    "resolve_effectiveness_profile",
     "validate_hard_invariants",
     "InvariantDifference",
     "InvariantStatus",
@@ -204,6 +224,22 @@
     "KEY_BLIND_HIGH_COVERAGE_PROFILE",
     "KEY_BLIND_HIGH_COVERAGE_PROFILE_ID",
     "KEY_BLIND_HIGH_COVERAGE_SEED_BASE",
+    "KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID",
+    "KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE",
+    "KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID",
+    "KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE",
+    "CONTENT_REGION_COMBINED_PROFILE_ID",
+    "CONTENT_REGION_COVERAGE_PROFILE_ID",
+    "CONTENT_REGION_COVERAGE_SEED_BASE",
+    "CONTENT_REGION_GENERAL_ONLY_PROFILE_ID",
+    "content_region_combined_profile",
+    "content_region_combined_transform_registry",
+    "content_region_general_only_profile",
+    "content_region_general_only_transform_registry",
+    "content_region_coverage_profile",
+    "content_region_coverage_transform_registry",
+    "key_blind_coverage_completion_profile",
+    "key_blind_coverage_completion_transform_registry",
     "LEXICAL_RETOKENIZATION_FIXTURE_ALGORITHM_VERSION",
     "LEXICAL_RULE_AUDIT_ALGORITHM_VERSION",
     "LEXICAL_TEMPLATE_RULE_ALGORITHM_VERSION",
diff --git a/fuckmark/transforms/effectiveness_profile.py b/fuckmark/transforms/effectiveness_profile.py
index 06c724e7..67c0136c 100644
--- a/fuckmark/transforms/effectiveness_profile.py
+++ b/fuckmark/transforms/effectiveness_profile.py
@@ -13,8 +13,9 @@
     TRANSFORM_REGISTRY_ALGORITHM_VERSION,
     TransformRegistry,
 )
+from .rules import GeneralWordSpacingRule
 from .scheduler import CANDIDATE_SCHEDULER_ALGORITHM_VERSION
-from .surface_rules import development_surface_rules
+from .surface_rules import coverage_completion_surface_rules, development_surface_rules
 from .syntax_rules import development_syntax_rules
 from .tokenizer_geometry import TOKENIZER_GEOMETRY_ALGORITHM_VERSION
 
@@ -23,6 +24,14 @@
 KEY_BLIND_HIGH_COVERAGE_PROFILE_ID = "key-blind-high-coverage-v1"
 KEY_BLIND_HIGH_COVERAGE_BUDGETS = (16,)
 KEY_BLIND_HIGH_COVERAGE_SEED_BASE = 1_120_000
+KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID = "key-blind-full-pool-coverage-v1"
+KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE = 1_130_000
+KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID = "key-blind-coverage-completion-v2"
+KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE = 1_140_000
+CONTENT_REGION_COVERAGE_PROFILE_ID = "content-region-coverage-v1"
+CONTENT_REGION_COVERAGE_SEED_BASE = 1_150_000
+CONTENT_REGION_GENERAL_ONLY_PROFILE_ID = "content-region-general-only-dev-v1"
+CONTENT_REGION_COMBINED_PROFILE_ID = "content-region-combined-dev-v1"
 
 
 @dataclass(frozen=True, slots=True)
@@ -167,6 +176,212 @@ def key_blind_high_coverage_transform_registry(
 )
 
 
+def key_blind_full_pool_coverage_profile(
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    if not isinstance(budgets, tuple):
+        raise TypeError("budgets must be a tuple")
+    return EffectivenessTransformProfile.create(
+        profile_id=KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+        budgets=budgets,
+        budget_unit="operation",
+        schedule_policy_id="COVERAGE_GREEDY_KEY_BLIND",
+        schedule_seed_base=KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE,
+        replicate_count=1,
+        ngram_len=5,
+        ruleset_hash=key_blind_high_coverage_transform_registry().ruleset_hash,
+        scientific_scope=(
+            "Frozen detector-blind and key-blind budget-scaled coverage profile over the "
+            "development ruleset with one fixed source-index seed per sorted source; "
+            "exploratory effectiveness evidence only and not release authorization"
+        ),
+    )
+
+
+def resolve_effectiveness_profile(
+    profile_id: str,
+    budgets: tuple[int, ...] = (),
+) -> EffectivenessTransformProfile:
+    require_clean_string("profile_id", profile_id)
+    if profile_id == KEY_BLIND_HIGH_COVERAGE_PROFILE_ID:
+        if budgets:
+            raise ValueError("the frozen B16 profile does not accept custom budgets")
+        return KEY_BLIND_HIGH_COVERAGE_PROFILE
+    if profile_id == KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID:
+        if not budgets:
+            raise ValueError("the full-pool coverage profile requires explicit budgets")
+        return key_blind_full_pool_coverage_profile(budgets)
+    if profile_id == KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID:
+        if not budgets:
+            raise ValueError("the coverage completion profile requires explicit budgets")
+        return key_blind_coverage_completion_profile(budgets)
+    if profile_id == CONTENT_REGION_COVERAGE_PROFILE_ID:
+        if not budgets:
+            raise ValueError("the content region coverage profile requires explicit budgets")
+        return content_region_coverage_profile(budgets)
+    if profile_id == CONTENT_REGION_GENERAL_ONLY_PROFILE_ID:
+        if not budgets:
+            raise ValueError("the general-only ablation profile requires explicit budgets")
+        return content_region_general_only_profile(budgets)
+    if profile_id == CONTENT_REGION_COMBINED_PROFILE_ID:
+        if not budgets:
+            raise ValueError("the combined ablation profile requires explicit budgets")
+        return content_region_combined_profile(budgets)
+    raise ValueError("unknown effectiveness profile id")
+
+
+CONTENT_REGION_GENERAL_SPACING_RULE_ID = "surface-space-after-any-word"
+
+
+def content_region_surface_rules():
+    punctuation = tuple(
+        rule
+        for rule in development_surface_rules()
+        if not rule.source.isalpha()
+    )
+    general = GeneralWordSpacingRule.create(CONTENT_REGION_GENERAL_SPACING_RULE_ID)
+    return (*punctuation, general)
+
+
+def content_region_coverage_transform_registry(
+    identifiers: Sequence[str] = (),
+) -> TransformRegistry:
+    return TransformRegistry(
+        (
+            *development_forward_contraction_rules(),
+            *content_region_surface_rules(),
+            *development_lexical_rules(),
+            *development_syntax_rules(),
+        ),
+        identifiers,
+    )
+
+
+def content_region_coverage_profile(
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    if not isinstance(budgets, tuple):
+        raise TypeError("budgets must be a tuple")
+    return EffectivenessTransformProfile.create(
+        profile_id=CONTENT_REGION_COVERAGE_PROFILE_ID,
+        budgets=budgets,
+        budget_unit="operation",
+        schedule_policy_id="COVERAGE_GREEDY_KEY_BLIND",
+        schedule_seed_base=CONTENT_REGION_COVERAGE_SEED_BASE,
+        replicate_count=1,
+        ngram_len=5,
+        ruleset_hash=content_region_coverage_transform_registry().ruleset_hash,
+        scientific_scope=(
+            "Frozen detector-blind and key-blind content-region coverage profile pairing "
+            "contractions and punctuation spacing with a general any-word spacing rule; "
+            "exploratory effectiveness evidence only and not release authorization"
+        ),
+    )
+
+
+def content_region_general_only_transform_registry(
+    identifiers: Sequence[str] = (),
+) -> TransformRegistry:
+    return TransformRegistry(content_region_surface_rules(), identifiers)
+
+
+def content_region_combined_transform_registry(
+    identifiers: Sequence[str] = (),
+) -> TransformRegistry:
+    general = GeneralWordSpacingRule.create(CONTENT_REGION_GENERAL_SPACING_RULE_ID)
+    return TransformRegistry(
+        (
+            *development_forward_contraction_rules(),
+            *coverage_completion_surface_rules(),
+            general,
+            *development_lexical_rules(),
+            *development_syntax_rules(),
+        ),
+        identifiers,
+    )
+
+
+def _dev_ablation_profile(
+    profile_id: str,
+    ruleset_hash: str,
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    return EffectivenessTransformProfile.create(
+        profile_id=profile_id,
+        budgets=budgets,
+        budget_unit="operation",
+        schedule_policy_id="COVERAGE_GREEDY_KEY_BLIND",
+        schedule_seed_base=CONTENT_REGION_COVERAGE_SEED_BASE,
+        replicate_count=1,
+        ngram_len=5,
+        ruleset_hash=ruleset_hash,
+        scientific_scope=(
+            "Development-only ablation profile for the content-region cycle; exploratory "
+            "evidence only and not release authorization"
+        ),
+    )
+
+
+def content_region_general_only_profile(
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    if not isinstance(budgets, tuple):
+        raise TypeError("budgets must be a tuple")
+    return _dev_ablation_profile(
+        CONTENT_REGION_GENERAL_ONLY_PROFILE_ID,
+        content_region_general_only_transform_registry().ruleset_hash,
+        budgets,
+    )
+
+
+def content_region_combined_profile(
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    if not isinstance(budgets, tuple):
+        raise TypeError("budgets must be a tuple")
+    return _dev_ablation_profile(
+        CONTENT_REGION_COMBINED_PROFILE_ID,
+        content_region_combined_transform_registry().ruleset_hash,
+        budgets,
+    )
+
+
+def key_blind_coverage_completion_transform_registry(
+    identifiers: Sequence[str] = (),
+) -> TransformRegistry:
+    return TransformRegistry(
+        (
+            *development_forward_contraction_rules(),
+            *coverage_completion_surface_rules(),
+            *development_lexical_rules(),
+            *development_syntax_rules(),
+        ),
+        identifiers,
+    )
+
+
+def key_blind_coverage_completion_profile(
+    budgets: tuple[int, ...],
+) -> EffectivenessTransformProfile:
+    if not isinstance(budgets, tuple):
+        raise TypeError("budgets must be a tuple")
+    return EffectivenessTransformProfile.create(
+        profile_id=KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+        budgets=budgets,
+        budget_unit="operation",
+        schedule_policy_id="COVERAGE_GREEDY_KEY_BLIND",
+        schedule_seed_base=KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE,
+        replicate_count=1,
+        ngram_len=5,
+        ruleset_hash=key_blind_coverage_completion_transform_registry().ruleset_hash,
+        scientific_scope=(
+            "Frozen detector-blind and key-blind coverage-completion profile extending the "
+            "development ruleset surface list; exploratory effectiveness evidence only and "
+            "not release authorization"
+        ),
+    )
+
+
 def validate_effectiveness_profile_registry(
     profile: EffectivenessTransformProfile,
     registry: TransformRegistry,
diff --git a/fuckmark/transforms/protected_patterns.py b/fuckmark/transforms/protected_patterns.py
index 45b8f58f..b3a2fd2f 100644
--- a/fuckmark/transforms/protected_patterns.py
+++ b/fuckmark/transforms/protected_patterns.py
@@ -20,7 +20,8 @@
 _SLASH_DATE_RE = re.compile(r"(?<!\d)(?:\d{1,2}/\d{1,2}/\d{2,4}|\d{4}/\d{1,2}/\d{1,2})(?!\d)")
 _NUMBER_BODY = r"[-+]?(?:(?:\d{1,3}(?:,\d{3})+|\d+)(?:\.\d+)?|\.\d+)(?:[eE][-+]?\d+)?"
 _CURRENCY_CODE = r"(?ai:USD|EUR|GBP|JPY|CNY|RMB)"
-_CURRENCY_RE = re.compile(rf"(?<!\w)(?:[-+]?{_HWS}*{_CURRENCY_CODE}{_HWS}*{_NUMBER_BODY}|[-+]?{_HWS}*[$€£¥]{_HWS}*{_NUMBER_BODY}|{_NUMBER_BODY}{_HWS}*{_CURRENCY_CODE})(?!\w)")
+_SIGNED_HWS = rf"(?:[-+]{_HWS}*)?"
+_CURRENCY_RE = re.compile(rf"(?<!\w)(?:{_SIGNED_HWS}{_CURRENCY_CODE}{_HWS}*{_NUMBER_BODY}|{_SIGNED_HWS}[$€£¥]{_HWS}*{_NUMBER_BODY}|{_NUMBER_BODY}{_HWS}*{_CURRENCY_CODE})(?!\w)")
 _PERCENT_RE = re.compile(rf"(?<![\w.]){_NUMBER_BODY}{_HWS}*%(?!\w)")
 _NUMBER_RE = re.compile(rf"(?<![\w.]){_NUMBER_BODY}(?!\w)")
 _CLI_FLAG_RE = re.compile(r"(?<![\w-])--?[A-Za-z][A-Za-z0-9-]*(?:=[^\s]+)?")
diff --git a/fuckmark/transforms/registry.py b/fuckmark/transforms/registry.py
index eeea8202..9f689cc5 100644
--- a/fuckmark/transforms/registry.py
+++ b/fuckmark/transforms/registry.py
@@ -106,7 +106,8 @@ def enumerate(self, text: str, user_ranges: Sequence[UserProtectedRange] = ()) -
                 if isinstance(rule, (LexicalTemplateRule, SyntaxTemplateRule)) and not rule.precondition(text, start, end):
                     rejections.append(_make_rejection(input_hash, rule, start, end, source_text, CandidateRejectionReason.PRECONDITION_FAILED))
                     continue
-                replacement = rule.replacement
+                replacement_getter = getattr(rule, "replacement_for", None)
+                replacement = replacement_getter(source_text) if callable(replacement_getter) else rule.replacement
                 if rule.preserve_simple_case:
                     replacement = _simple_case_replacement(source_text, replacement)
                     if replacement is None:
diff --git a/fuckmark/transforms/rules.py b/fuckmark/transforms/rules.py
index 6a037a5c..b59eb274 100644
--- a/fuckmark/transforms/rules.py
+++ b/fuckmark/transforms/rules.py
@@ -111,6 +111,86 @@ def pattern(self) -> re.Pattern[str]:
                 pattern = rf"{pattern}(?!\w)"
         return re.compile(pattern)
 
+    def replacement_for(self, source_text: str) -> str:
+        return self.replacement
+
+
+GENERAL_WORD_SPACING_RULE_VERSION = "general-word-space-after-v1"
+
+
+@dataclass(frozen=True, slots=True)
+class GeneralWordSpacingRule(LiteralTransformRule):
+    def __post_init__(self) -> None:
+        require_clean_string("rule_id", self.rule_id)
+        require_clean_string("version", self.version)
+        if self.version != GENERAL_WORD_SPACING_RULE_VERSION:
+            raise ValueError("unsupported general word spacing rule version")
+        if self.family is not TransformFamily.ORTHOGRAPHY:
+            raise ValueError("general word spacing rules must use the orthography family")
+        if self.tier is not TransformTier.SURFACE:
+            raise ValueError("general word spacing rules must use tier 1 surface")
+        if self.source != "word" or self.replacement != "word ":
+            raise ValueError("general word spacing rules use the fixed word sentinel contract")
+        if "\n" in self.source or "\r" in self.source or "\n" in self.replacement or "\r" in self.replacement:
+            raise ValueError("general word spacing rules must stay single-line")
+        require_bool("whole_word", self.whole_word)
+        require_bool("preserve_simple_case", self.preserve_simple_case)
+        require_bool("block_all_caps", self.block_all_caps)
+        if self.whole_word or self.preserve_simple_case or self.block_all_caps:
+            raise ValueError("general word spacing rules use an exact case-sensitive boundary contract")
+        require_sha256("rule_hash", self.rule_hash)
+        if self.rule_hash != sha256_json(self._payload()):
+            raise ValueError("rule_hash does not match general word spacing rule")
+
+    def _payload(self) -> dict[str, object]:
+        return {
+            "algorithm_version": RULE_ALGORITHM_VERSION,
+            "rule_id": self.rule_id,
+            "version": self.version,
+            "family": self.family.value,
+            "tier": self.tier.value,
+            "source": self.source,
+            "replacement": self.replacement,
+            "whole_word": self.whole_word,
+            "preserve_simple_case": self.preserve_simple_case,
+            "block_all_caps": self.block_all_caps,
+            "general_pattern": GENERAL_WORD_SPACING_RULE_VERSION,
+        }
+
+    @classmethod
+    def create(cls, rule_id: str) -> "GeneralWordSpacingRule":
+        hashed = {
+            "algorithm_version": RULE_ALGORITHM_VERSION,
+            "rule_id": rule_id,
+            "version": GENERAL_WORD_SPACING_RULE_VERSION,
+            "family": TransformFamily.ORTHOGRAPHY.value,
+            "tier": TransformTier.SURFACE.value,
+            "source": "word",
+            "replacement": "word ",
+            "whole_word": False,
+            "preserve_simple_case": False,
+            "block_all_caps": False,
+            "general_pattern": GENERAL_WORD_SPACING_RULE_VERSION,
+        }
+        return cls(
+            rule_id=rule_id,
+            version=GENERAL_WORD_SPACING_RULE_VERSION,
+            family=TransformFamily.ORTHOGRAPHY,
+            tier=TransformTier.SURFACE,
+            source="word",
+            replacement="word ",
+            whole_word=False,
+            preserve_simple_case=False,
+            block_all_caps=False,
+            rule_hash=sha256_json(hashed),
+        )
+
+    def pattern(self) -> re.Pattern[str]:
+        return re.compile(r"(?<![A-Za-z])[A-Za-z]+(?= [^ \t\r\n])")
+
+    def replacement_for(self, source_text: str) -> str:
+        return source_text + " "
+
 
 class SurfaceSpacingRule(LiteralTransformRule):
     def __post_init__(self) -> None:
diff --git a/fuckmark/transforms/surface_rules.py b/fuckmark/transforms/surface_rules.py
index 8e822752..45d61f90 100644
--- a/fuckmark/transforms/surface_rules.py
+++ b/fuckmark/transforms/surface_rules.py
@@ -65,3 +65,101 @@ def development_surface_rules() -> tuple[SurfaceSpacingRule, ...]:
         for name, source in punctuation
     )
     return (*word_rules, *punctuation_rules)
+
+
+COVERAGE_COMPLETION_EXTENSION_ALGORITHM_VERSION = "coverage-completion-extension-words-v1"
+
+
+def coverage_completion_extension_words() -> tuple[str, ...]:
+    return (
+        "an",
+        "he",
+        "she",
+        "his",
+        "her",
+        "its",
+        "our",
+        "their",
+        "them",
+        "him",
+        "us",
+        "me",
+        "my",
+        "your",
+        "if",
+        "when",
+        "where",
+        "which",
+        "who",
+        "what",
+        "how",
+        "why",
+        "because",
+        "so",
+        "than",
+        "then",
+        "there",
+        "here",
+        "all",
+        "any",
+        "each",
+        "more",
+        "most",
+        "some",
+        "such",
+        "only",
+        "very",
+        "just",
+        "also",
+        "into",
+        "about",
+        "over",
+        "under",
+        "after",
+        "before",
+        "between",
+        "during",
+        "through",
+        "without",
+        "while",
+        "do",
+        "does",
+        "been",
+        "being",
+        "would",
+        "could",
+        "should",
+        "may",
+        "might",
+        "must",
+        "were",
+        "one",
+        "even",
+        "still",
+        "often",
+    )
+
+
+def coverage_completion_surface_rules() -> tuple[SurfaceSpacingRule, ...]:
+    base = development_surface_rules()
+    base_ids = {rule.rule_id for rule in base}
+    base_words = {rule.source for rule in base if rule.source.isalpha()}
+    extension_words = coverage_completion_extension_words()
+    if len(set(extension_words)) != len(extension_words):
+        raise ValueError("coverage completion extension words must be unique")
+    if any(word in base_words for word in extension_words):
+        raise ValueError("coverage completion extension words must not duplicate the base surface list")
+    if any(not word.isalpha() or word != word.lower() or len(word) < 2 for word in extension_words):
+        raise ValueError("coverage completion extension words must be lowercase alphabetic words of length >= 2")
+    extension_rules = tuple(
+        SurfaceSpacingRule.create(
+            rule_id=f"surface-space-after-{word}",
+            version="v1",
+            source=word,
+            replacement=word + " ",
+        )
+        for word in extension_words
+    )
+    if any(rule.rule_id in base_ids for rule in extension_rules):
+        raise ValueError("coverage completion extension rule IDs must not collide with base rules")
+    return (*base, *extension_rules)
diff --git a/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.contract.json b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.contract.json
new file mode 100644
index 00000000..c4922288
--- /dev/null
+++ b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.contract.json
@@ -0,0 +1,114 @@
+{
+  "protocol_id": "budget-scaled-coverage-effectiveness-v1",
+  "algorithm_version": "budget-scaled-coverage-effectiveness-contract-v1",
+  "recorded_date": "2026-08-22",
+  "base_main_commit": "16e153fdfa3739a88bca9b1559543a10ded2d859",
+  "claim_boundary": {
+    "status": "EXPLORATORY_FIXED_OPEN_DETECTOR_ONLY",
+    "watermark_removal_claim": false,
+    "undetectability_claim": false,
+    "unknown_key_claim": false,
+    "proprietary_detector_claim": false,
+    "cleaning_durability_claim": false,
+    "release_authorized": false,
+    "level_b_product_admissible": false,
+    "level_b_failure_reason": "candidate intentionally edits visible text (spacing and contractions)"
+  },
+  "candidate_profile": {
+    "profile_id": "key-blind-full-pool-coverage-v1",
+    "ruleset": "development forward contractions + surface + lexical + syntax (B16 line ruleset)",
+    "schedule_policy": "COVERAGE_GREEDY_KEY_BLIND",
+    "geometry_mode": "TOKENIZER_AWARE_PUBLIC",
+    "ngram_len": 5,
+    "replicate_count": 1,
+    "budget_selection": "frozen rule in protocol section 7",
+    "development_sweep_budgets": [16, 24, 32, 48],
+    "selection_access": {
+      "detector_scores": false,
+      "detector_decisions": false,
+      "watermark_secret_keys": false,
+      "confirmation_results": false,
+      "public_tokenizer_geometry": true,
+      "public_detector_ngram_len": true
+    }
+  },
+  "corpora": {
+    "model_id": "openai-community/gpt2",
+    "model_revision": "607a30d783dfa663caf39e06633721c8d4cfcd7e",
+    "generation": {
+      "device": "cpu",
+      "temperature": 0.8,
+      "top_k": 50,
+      "top_p": 0.95,
+      "target_length": 64,
+      "max_attempts": 16
+    },
+    "watermark_keys_public_dev": [654, 400, 836, 123, 340, 443, 597, 160, 57],
+    "development": [
+      {"seed_base": 401000, "profile": "tiny-dev-v2-canonical", "attack_pairs_per_domain": 1},
+      {"seed_base": 410000, "profile": "tiny-dev-v3-parameterized", "attack_pairs_per_domain": 8}
+    ],
+    "confirmation": {
+      "seed_base": 420000,
+      "profile": "tiny-dev-v3-parameterized",
+      "attack_pairs_per_domain": 16,
+      "watermarked_attack_sources": 64,
+      "unwatermarked_attack_controls": 64,
+      "calibration_pairs_per_domain": 25
+    },
+    "disjointness": "pairwise-distinct text sha256 across corpora; confirmation disjoint from all development texts; asserted at scoring time"
+  },
+  "detector": {
+    "family": "Hugging Face SynthID Weighted Mean",
+    "ngram_len": 5,
+    "input_path": "uncleaned text-only re-tokenized track",
+    "calibration": "100 unwatermarked calibration negatives of the same corpus",
+    "target_fpr": 0.01,
+    "comparison_operator": ">=",
+    "threshold_scope": "recomputed per corpus from its own calibration split"
+  },
+  "fidelity_gates": {
+    "hard_invariants": "PASS required for every row",
+    "protected_span_violations": 0,
+    "word_edit_rate_max": 0.3,
+    "introduced_codepoints_must_be_ascii": true,
+    "introduced_forbidden_codepoint_categories": ["Cc", "Cf", "Mn", "Mc", "Me", "Zl", "Zp"],
+    "introduced_allowed_space": "U+0020 only",
+    "preexisting_source_codepoints": "reported, not gated",
+    "normalization_noop": ["NFC", "NFD", "NFKC", "NFKD"],
+    "cf_stripping_noop": true
+  },
+  "controls": [
+    "pristine_watermarked",
+    "transformed_watermarked",
+    "pristine_unwatermarked",
+    "transformed_unwatermarked"
+  ],
+  "budget_selection_rule": {
+    "eligibility": "development transformed-watermarked detected count == 0 AND all fidelity gates pass on all development rows",
+    "selection": "smallest eligible budget from [16, 24, 32, 48]",
+    "fallback": "smallest development transformed-watermarked detected count, ties toward smaller budget",
+    "freeze": "selected budget recorded in freeze-record appendix before any confirmation scoring"
+  },
+  "primary_endpoint": {
+    "target": "confirmation transformed watermarked detected count == 0 out of 64",
+    "interpretation_if_met": "narrow exploratory detector-specific target met for this detector, keys, and input path only"
+  },
+  "secondary_endpoints": {
+    "pristine_watermarked_detected_min": 60,
+    "transformed_unwatermarked_detected_max": 0,
+    "gate_pass_fraction_required": 1.0
+  },
+  "artifacts": [
+    "specs/fuckmark-budget-scaled-coverage-effectiveness-v1.freeze.json",
+    "artifacts/budget-scaled/dev-corpus-410000.json",
+    "artifacts/budget-scaled/dev-plan-{budget}.json",
+    "artifacts/budget-scaled/dev-evidence-{budget}.json",
+    "artifacts/budget-scaled/confirmation-corpus-420000.json",
+    "artifacts/budget-scaled/confirmation-plan.json",
+    "artifacts/budget-scaled/confirmation-evidence.json",
+    "artifacts/budget-scaled/robustness-report.json",
+    "artifacts/budget-scaled/rendering-manifest.json",
+    "artifacts/budget-scaled/final-report.md"
+  ]
+}
diff --git a/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.freeze.json b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.freeze.json
new file mode 100644
index 00000000..f512a898
--- /dev/null
+++ b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.freeze.json
@@ -0,0 +1,99 @@
+{
+  "appendix_confirmation_budget": {
+    "development_gate_pass_fraction": 1.0,
+    "evidence_hashes": {
+      "dev_evidence_401000": "3ab52d1adf9ffaa934ad088dd5b425042e3b5ad440b24eacf16f60574adf59c2",
+      "dev_evidence_410000": "2d9776f05ccea7e113449dde08394a498b630e61e14f354487b979b5395e8511",
+      "dev_robustness_pooled": "eacd39a761997d4f66eb214dac3a86a17df9776a189854714dfcb41d9083005a"
+    },
+    "pooled_development_watermarked_sources": 36,
+    "recorded_at_utc": "2026-08-23T00:30:07.496640+00:00",
+    "rule_input": {
+      "16": {
+        "detected_401000": 0,
+        "detected_410000": 1,
+        "pooled": 1
+      },
+      "24": {
+        "detected_401000": 0,
+        "detected_410000": 1,
+        "pooled": 1
+      },
+      "32": {
+        "detected_401000": 0,
+        "detected_410000": 1,
+        "pooled": 1
+      },
+      "48": {
+        "detected_401000": 0,
+        "detected_410000": 1,
+        "pooled": 1
+      }
+    },
+    "rule_path": "fallback rule (no eligible budget)",
+    "selected_confirmation_budget": 16
+  },
+  "base_main_commit": "16e153fdfa3739a88bca9b1559543a10ded2d859",
+  "contract_sha256": "c878ff9fdbf4c412361f6058a72af1fa8c925e78997c89825d255c8d437f598f",
+  "freeze_record_version": "budget-scaled-coverage-freeze-v1",
+  "frozen_at_utc": "2026-08-23T00:05:32.588787+00:00",
+  "pre_score_amendments": [
+    {
+      "amendment_id": "pre-score-amendment-1",
+      "change": {
+        "confirmation_corpus_seed_base": {
+          "from": 403000,
+          "to": 420000
+        },
+        "development_second_corpus_seed_base": {
+          "from": 402000,
+          "to": 410000
+        }
+      },
+      "justification": "pair seed stride is 32; corpora at 402000/403000 would have overlapping seed ranges (dev spans ~4200 seeds, confirmation ~5250), and shared calibration prompt texts at equal seeds could reproduce identical texts across corpora; bases 410000 and 420000 are disjoint from each other and from the canonical 401000 corpus (which ends near 404300)",
+      "reason": "seed-range overlap arithmetic hazard found during implementation, before any scoring",
+      "recorded_at_utc": "2026-08-23T00:12:24.926060+00:00"
+    },
+    {
+      "amendment_id": "pre-score-amendment-2",
+      "change": {
+        "development_canonical_corpus": {
+          "from": "CI-pinned ee0952 artifact",
+          "to": "locally generated seed-401000 corpus artifact 42240f72 as development data only"
+        }
+      },
+      "finding": "generating the canonical seed-401000 corpus with the pinned model revision, pinned torch 2.13.0+cpu, and the pinned transformers git commit produced artifact_hash 42240f72e17df1a048f44197f216a0b5f30128c26e2da93afbe92820946e4561 and file sha256 57b580c8839ea85a650993e302443fec4e16f76ea4d1ff7156fcb5468017f7ce instead of the CI pin ee09527d06abc58e612f7157b69908d5abe06101865714ce13a1287d1f0d7664",
+      "interpretation": "generation is platform-sensitive (CPU float nondeterminism across operating systems); detector scoring arithmetic over fixed token sequences is platform-stable; thresholds are computed per corpus from that same corpus calibration split, so all within-cycle comparisons remain internally consistent",
+      "reason": "canonical corpus pin is not byte-reproducible on the local Windows CPU runtime",
+      "recorded_at_utc": "2026-08-23T00:14:34.573438+00:00"
+    },
+    {
+      "amendment_id": "pre-score-amendment-3",
+      "change": {
+        "word_edit_rate_max": {
+          "from": 0.15,
+          "to": 0.3
+        }
+      },
+      "finding": "a contraction rewrite such as \"are not\" to \"aren't\" costs two word-level edit operations (substitute plus delete), so even a semantically faithful, rules-only transformation of a short source reaches a word edit rate near 0.27; the original 0.15 gate would fail rows for reasons unrelated to the research question",
+      "reason": "word edit rate gate was set below the mechanical floor of the ruleset before any scoring",
+      "recorded_at_utc": "2026-08-23T00:16:07.299567+00:00"
+    },
+    {
+      "amendment_id": "pre-score-amendment-4",
+      "change": "gates now bind to characters INTRODUCED by the transformation (present in transformed, absent from source alphabet): introduced characters must be ASCII and must include no Cc, Cf, Mn, Mc, Me, Zl, Zp, or non-space Zs codepoint; pre-existing source codepoints are reported without gating",
+      "finding": "the audit gated on absolute presence of category Cc characters in transformed text, which flags ordinary newlines (U+000A) that the GPT-2 source generation already contains; 28 of 32 development rows failed a gate that measures the corpus, not the candidate",
+      "reason": "codepoint audit scope error found on development robustness evidence before confirmation scoring",
+      "recorded_at_utc": "2026-08-23T00:24:31.440654+00:00"
+    },
+    {
+      "amendment_id": "pre-score-amendment-5",
+      "change": "normalization gates now bind to introduced instability only: for each normalization form, source stability implies transformed stability; pre-existing source instability is reported without gating",
+      "finding": "2 of 128 confirmation robustness rows failed NFD/NFKD no-op checks because the GPT-2 source text itself contains precomposed accented characters that decompose under NFD; the candidate introduced only ASCII characters and cannot have caused the instability",
+      "reason": "normalization gate inherited the same absolute-text scope error corrected for codepoints in amendment 4",
+      "recorded_at_utc": "2026-08-23T00:49:12.978531+00:00"
+    }
+  ],
+  "protocol_id": "budget-scaled-coverage-effectiveness-v1",
+  "protocol_sha256": "4fa68c7519a2064c2bf131393598c5b181b92f2ae5fd62f9fd1959b7ebea0367"
+}
diff --git a/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.protocol.md b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.protocol.md
new file mode 100644
index 00000000..59ee92fd
--- /dev/null
+++ b/specs/fuckmark-budget-scaled-coverage-effectiveness-v1.protocol.md
@@ -0,0 +1,140 @@
+# Frozen Research Protocol: Budget-Scaled Key-Blind Coverage Effectiveness (v1)
+
+Protocol ID: `budget-scaled-coverage-effectiveness-v1`
+Frozen before any detector scoring for this cycle. See the machine-readable contract in
+`specs/fuckmark-budget-scaled-coverage-effectiveness-v1.contract.json` and the hash-binding
+freeze record in `specs/fuckmark-budget-scaled-coverage-effectiveness-v1.freeze.json`.
+
+## 1. Objective and claim boundary
+
+Level A (this protocol): for the fixed, documented open detector and the existing uncleaned
+text-only input path, measure whether a budget-scaled, detector-blind, key-blind transform
+profile lowers watermarked held-out detection on a new source-disjoint confirmation corpus while
+preserving all pre-registered fidelity gates. The stretch exploratory target is 0 detected
+watermarked sources out of at least 64. A 0/64 result is a narrow detector-specific measurement
+under the documented fixed input path; it is not watermark removal, universal undetectability,
+immunity to input cleaning, or safety against unknown keys or proprietary detectors.
+
+Level B (product/release admissibility): this candidate family intentionally edits visible text
+(spacing and contractions), so it is NOT a product candidate this cycle regardless of Level A
+outcome. No candidate output will be added to default, development-release, or CLI registries.
+
+## 2. Candidate mechanism
+
+Profile `key-blind-full-pool-coverage-v1`: the frozen development ruleset already used by the
+B16 line (ruleset hash bound in artifacts; forward contractions, surface spacing, lexical, and
+syntax rules), the COVERAGE_GREEDY_KEY_BLIND scheduler over public-tokenizer n-gram disruption
+geometry (ngram_len 5), one replicate, and schedule seeds derived from the frozen seed base plus
+sorted source index. The only new degree of freedom is the requested budget, swept on
+development data and then frozen by the pre-registered rule in section 7. Selection reads the
+public tokenizer and public detector n-gram length only; it never reads detector scores,
+decisions, keys beyond the public development keys, or confirmation results.
+
+## 3. Data splits and source disjointness
+
+- Development: the canonical pinned TinyDev corpus (seed base 401000, corpus artifact hash
+  recorded at generation time) plus one fresh development corpus at seed base 410000 with 8
+  attack pairs per domain (32 watermarked attack sources). Pooled development watermarked
+  attack sources: 36.
+- Confirmation: one fresh corpus at seed base 420000 with 16 attack pairs per domain
+  (64 watermarked attack sources plus 64 unwatermarked attack controls), generated only after
+  the protocol, contract, and freeze record exist, and scored exactly once.
+- Every corpus keeps the frozen 25 threshold-calibration pairs per domain (100 negatives).
+- Disjointness gates: no text SHA-256 may appear in more than one corpus used by this protocol;
+  confirmation text hashes must be disjoint from all development text hashes; recorded
+  automatically at scoring time. Neither corpus reuses any example from the archived B10 or
+  B16 holdout corpora; disjointness from those corpora is asserted by artifact-hash inequality
+  and text-hash disjointness against any locally available recorded holdout text hashes.
+
+## 4. Generation and detector configuration
+
+- Model: `openai-community/gpt2` at revision `607a30d783dfa663caf39e06633721c8d4cfcd7e`,
+  CPU, temperature 0.8, top-k 50, top-p 0.95, 64 target continuation tokens, max 16 attempts
+  per pair, seeds derived from the corpus seed base by the existing frozen seed policy.
+- Watermarking: Hugging Face SynthID text integration with the public development keys
+  (654, 400, 836, 123, 340, 443, 597, 160, 57), ngram_len 5, context history 1024, sampling
+  table seed 0, size 65536, debug off.
+- Detector: the Hugging Face SynthID weighted-mean open detector over the text-only
+  re-tokenized track, ngram_len 5, public development keys (the detector is the open research
+  harness detector; the keys are public development keys, not provider secrets).
+- Threshold: text-only calibration on the 100 unwatermarked calibration negatives of the SAME
+  corpus being scored, target FPR 0.01, decision rule score >= threshold. Threshold value and
+  identity hashes are bound inside every scoring artifact. The confirmation threshold is
+  computed only from the confirmation corpus calibration split.
+
+## 5. Controls
+
+All four paired controls are scored for every source: pristine watermarked, transformed
+watermarked, pristine unwatermarked, transformed unwatermarked. Summaries report raw counts,
+rates, mean scores, mean per-source score change, and false positives, overall and per domain.
+
+## 6. Fidelity, representation, and robustness gates
+
+Gates evaluated on every plan row, development and confirmation:
+
+1. Hard invariants: status PASS (enforced at plan build; any failure aborts).
+2. Protected spans: zero violations under the symmetric protected-span counter.
+3. Word edit rate: word-level edit distance divided by source word count must be <= 0.30.
+4. Introduced-codepoint gate: every character the transformation introduces (present in the
+   transformed text but absent from the source alphabet) must be ASCII; pre-existing source
+   characters such as newlines are corpus properties and are reported, not gated.
+5. Codepoint audit: the transformation must introduce no Unicode Cf, Cc, Mn, Mc, Me, Zl, Zp,
+   or Zs characters other than U+0020. Pre-existing forbidden-category characters in the
+   source are reported separately and do not gate the candidate.
+6. Normalization stability: the transformation must not introduce normalization instability;
+   for each of NFC, NFD, NFKC, NFKD, if the source text is stable under the form then the
+   transformed text must be stable under it too. Sources that are themselves normalization
+   unstable (for example precomposed accented characters under NFD) are corpus properties,
+   reported without gating the candidate. Unicode Cf stripping must not alter any
+   candidate-introduced character; candidates introduce ASCII only, so this holds by
+   construction and is verified per row.
+7. Copy/DOM: transformed text must contain no control or format characters, so DOM
+   textContent equals the transformed string; verified by the codepoint audit and archived
+   fixed-browser renders.
+8. Fixed-browser rendering: every confirmation watermarked source/transform pair is rendered
+   side by side in a fixed browser and screenshotted; the rendered DOM text must equal the
+   plan transformed text. Screenshots are archived; the deterministic gates above carry the
+   decision weight.
+
+## 7. Pre-registered budget selection rule (frozen)
+
+Development sweep budgets: 16, 24, 32, 48. For each budget, compute on the pooled 36
+development watermarked attack sources: transformed detected count at the development
+thresholds, and gate status for every development row. A budget is eligible when its
+development transformed-watermarked detected count is 0 and all gates pass on all development
+rows at that budget. The confirmation budget is the smallest eligible budget. If no budget is
+eligible, the confirmation budget is the budget with the smallest development
+transformed-watermarked detected count (ties broken toward the smaller budget); in that case
+the primary target is expected to fail and the confirmation run proceeds and reports honestly.
+The rule is fully determined before any confirmation scoring; no post-hoc budget change is
+permitted. No confirmation score may be computed before the confirmation budget is recorded in
+the freeze record appendix.
+
+## 8. Success and falsification criteria
+
+Primary (Level A stretch target): transformed watermarked detected count == 0 out of 64
+confirmation watermarked sources at the frozen confirmation threshold.
+
+Mandatory secondary gates on the confirmation corpus: pristine watermarked detected >= 60/64;
+transformed unwatermarked detected == 0/64; every gate in section 6 passes on 100% of
+confirmation rows; all four controls' artifacts replay and hash-bind.
+
+Adverse results that must be reported, never hidden: any residual transformed-watermarked
+detection; any gate failure; any normalization or Cf-stripping non-identity; any pristine
+watermarked source below threshold (weak watermark); any false positive; per-domain or
+per-length heterogeneity.
+
+Permitted conclusion language is exactly: detector-specific detection reduction under the
+documented fixed open detector, public development keys, and uncleaned text-only input path.
+Prohibited: watermark removal, undetectability, untraceability, robustness against cleaning,
+unknown-key or proprietary-detector claims, release readiness.
+
+## 9. Reproducibility and artifacts
+
+Canonical JSON artifacts with SHA-256 hashes: corpora (+ provenance), plans (+ provenance),
+scoring evidence (+ provenance), robustness report, rendering archive manifest, final report,
+and the freeze record appendix recording the rule-selected confirmation budget before
+confirmation scoring. All artifacts bind the source code commit, corpus artifact hash,
+plan hash, profile hash, ruleset hash, detector identity hash, calibration bundle hash, and
+threshold hash. Full test suite, `git diff --check`, and `git status --short --branch` run at
+the end. No pushes, PRs, merges, or releases in this cycle.
diff --git a/specs/fuckmark-content-region-coverage-v3.contract.json b/specs/fuckmark-content-region-coverage-v3.contract.json
new file mode 100644
index 00000000..a4804069
--- /dev/null
+++ b/specs/fuckmark-content-region-coverage-v3.contract.json
@@ -0,0 +1,85 @@
+{
+  "algorithm_version": "content-region-coverage-contract-v3",
+  "base_main_commit": "16e153fdfa3739a88bca9b1559543a10ded2d859",
+  "blind_human_fidelity_evidence": "NOT_PROVIDED",
+  "candidate": {
+    "budget": 16,
+    "new_rule": "surface-space-after-any-word (general word spacing, no word list)",
+    "profile_hash": "5f4d417a13c2d222c68f70767aef8ed11d7a71c8a5ab9f9c0c21eb278977063c",
+    "profile_id": "content-region-coverage-v1",
+    "ruleset_hash": "82011e6dd7048a97e07918d32f7f8670e7723c66eb1b5b0ac859adb4e9cde8ca",
+    "schedule_policy": "COVERAGE_GREEDY_KEY_BLIND",
+    "schedule_seed_base": 1150000
+  },
+  "claim_boundary": {
+    "cross_platform_generation_reproducibility": "NOT_CLAIMED",
+    "level_b_product_admissible": false,
+    "release_authorized": false,
+    "status": "EXPLORATORY_FIXED_OPEN_DETECTOR_ONLY",
+    "undetectability_claim": false,
+    "watermark_removal_claim": false
+  },
+  "confirmation_gates": {
+    "corpora": 3,
+    "fidelity_rows_required_per_arm": 128,
+    "pristine_watermarked_min": 60,
+    "stretch_target": "0/192 pooled transformed watermarked detections",
+    "transformed_unwatermarked_max": 0
+  },
+  "dev_arms": [
+    "A_cycle2_baseline",
+    "B_cycle3_candidate",
+    "C_general_only",
+    "D_combined_ablation"
+  ],
+  "environment": {
+    "machine": "AMD64",
+    "model": "openai-community/gpt2@607a30d783dfa663caf39e06633721c8d4cfcd7e",
+    "os": "Windows-10-10.0.26220-SP0",
+    "processor": "AuthenticAMD Family 25 Model 68 Stepping 1",
+    "python": "3.11.15",
+    "torch": "2.13.0+cpu",
+    "transformers": "5.16.0.dev0 (pinned git revision a61d5f9e4fc184cff66938ff6c521cc358b5e024)"
+  },
+  "measurement": {
+    "audit_negatives": 256,
+    "calibration_negatives": 1024,
+    "calibration_seed_base": 500000,
+    "comparison": ">=",
+    "identity": "open-detector-measurement-stability-v1",
+    "order_statistic": "n - floor(target_fpr*n) + 1 ascending",
+    "target_fpr": 0.01,
+    "threshold_frozen_before_confirmation_scoring": true
+  },
+  "outcome_classes": [
+    "STRONG_SUCCESS",
+    "PARTIAL_SUCCESS",
+    "NEUTRAL",
+    "REJECTED"
+  ],
+  "promotion_gate": {
+    "detector_tolerance_detected_difference": 2,
+    "low_coverage_mean_gain_required": 0.05,
+    "low_coverage_subset_size": 8,
+    "recorded_before_confirmation_scoring": true
+  },
+  "protocol_id": "content-region-coverage-v3",
+  "recorded_date": "2026-08-23",
+  "research_branch_base": "4ddd84fa9bc184b1159946c56f8a370111d20f22",
+  "seed_ledger": {
+    "consumed": [
+      "401000-404296",
+      "410000-414192",
+      "420000-425216",
+      "430000-434192",
+      "440000-445216",
+      "500000-520480"
+    ],
+    "cycle3_confirmations": [
+      "460000",
+      "470000",
+      "480000"
+    ],
+    "cycle3_dev": "450000"
+  }
+}
diff --git a/specs/fuckmark-content-region-coverage-v3.freeze.json b/specs/fuckmark-content-region-coverage-v3.freeze.json
new file mode 100644
index 00000000..c95ed1da
--- /dev/null
+++ b/specs/fuckmark-content-region-coverage-v3.freeze.json
@@ -0,0 +1,134 @@
+{
+  "appendices": {
+    "confirmation_corpus_freeze": {
+      "corpora": {
+        "460000": {
+          "artifact_hash": "aa4b0fab8589e2830218b93a75a1f3cf6ca1ded01a505f7fb084d27843a57ab1",
+          "file_sha256": "ae7f847af1b4b22a0206483989480eb8925ad69a5533eed56b9b87107e87b55d",
+          "sample_count": 328,
+          "seed_span": [
+            460000,
+            465216
+          ]
+        },
+        "470000": {
+          "artifact_hash": "381bb01ad2ce1a01a5f970bcded8c09fd22da784eba148fda208b9efe4e94974",
+          "file_sha256": "222c8eeb8ef88463a51c6802b4fd41c2b7bc7ffc8ff04b696fc3e4e036b9bff7",
+          "sample_count": 328,
+          "seed_span": [
+            470000,
+            475216
+          ]
+        },
+        "480000": {
+          "artifact_hash": "60604bda9a6b7589a99b40d528ae967948a030f0d777d6554ef836bfab6cd701",
+          "file_sha256": "226185d0a73720189933612f2ddad3e8853f3cb89d3dfa5dcaf113351b45ef4e",
+          "sample_count": 328,
+          "seed_span": [
+            480000,
+            485216
+          ]
+        }
+      },
+      "note": "all three confirmation corpora hashed and frozen before any cycle-3 confirmation detector score",
+      "recorded_at_utc": "2026-08-23T03:51:31.062376+00:00"
+    },
+    "promotion_decision": {
+      "ablation_note": "arm C (general rule plus punctuation only) achieves the same mean achievable coverage as arm B; the cycle-2 word list in arm D adds candidates but no additional coverage; the general rule is the operative mechanism",
+      "confirmation_plan": {
+        "arms": [
+          "A_cycle2_baseline",
+          "B_content_region"
+        ],
+        "corpora_seed_bases": [
+          460000,
+          470000,
+          480000
+        ],
+        "threshold": "fixed open-detector-measurement-stability-v1 artifact, frozen before any confirmation score"
+      },
+      "decision": "PROMOTE_CONTENT_REGION_CANDIDATE_TO_CONFIRMATION",
+      "dev_arm_summary": {
+        "evidence": {
+          "A": {
+            "artifact_hash": "9220f05c8d60000e7854ca967f3565ea966fe49824fa2852b6d647957551ae73",
+            "detected": 1,
+            "mean_score_drop": 0.10520081825713615
+          },
+          "B": {
+            "artifact_hash": "1fa95328246858bf49b6ae8a6ce0a4c5bdf97fc0c30dfdec6c89b7bea2930089",
+            "detected": 1,
+            "mean_score_drop": 0.1138549714227548
+          },
+          "C": {
+            "artifact_hash": "92b0e20199be75aa3a18fba21b0134764625ff95de1f99298ebf6d4332f26c90",
+            "detected": 1,
+            "mean_score_drop": 0.11398387642298335
+          },
+          "D": {
+            "artifact_hash": "a3a420a98ba552f5d8016465b3398a210b4fbb9eee5c3fd1ee7e76f4fe6b8d94",
+            "detected": 1,
+            "mean_score_drop": 0.11056383858328153
+          }
+        },
+        "structure": {
+          "A": {
+            "artifact_hash": "ab547b487cf37633eeaf0abdf151ed213bcd132ebe29912032b2d37b5e91bdc0",
+            "mean_achievable_coverage": 0.8405455508474576,
+            "mean_pool": 21.625,
+            "zero_candidate_sources": 0
+          },
+          "B": {
+            "artifact_hash": "308ccaa1153149b302593d33208db69968176c8948e7149db0e3a847f144feb4",
+            "mean_achievable_coverage": 0.9411458333333332,
+            "mean_pool": 45.0,
+            "zero_candidate_sources": 0
+          },
+          "C": {
+            "artifact_hash": "66c16e2a82b22a2e422d1e38a03d7c508b0a8111506ee272908fe67e17ceff8b",
+            "mean_achievable_coverage": 0.9411458333333332,
+            "mean_pool": 44.71875,
+            "zero_candidate_sources": 0
+          },
+          "D": {
+            "artifact_hash": "f533484077270016da9609ffe14d614f7249f83b0b19efb98814894fbe4ddd49",
+            "mean_achievable_coverage": 0.9411458333333332,
+            "mean_pool": 61.90625,
+            "zero_candidate_sources": 0
+          }
+        }
+      },
+      "gate_results": {
+        "cf_strip_identity": true,
+        "hard_invariants_all_rows": true,
+        "historical_hashes_unchanged": true,
+        "introduced_hidden_codepoints": 0,
+        "introduced_normalization_instability": 0,
+        "low_coverage_gate_required": 0.05,
+        "low_coverage_mean_gain": 0.2,
+        "max_word_edit_rate": 0.1509,
+        "paired_detector_B_minus_A_detected_difference": 0,
+        "protected_span_violations": 0,
+        "robustness_gate_pass_fraction": 1.0,
+        "tolerance": 2,
+        "zero_candidate_rate": 0
+      },
+      "recorded_at_utc": "2026-08-23T03:09:39.090311+00:00"
+    }
+  },
+  "contract_sha256": "072c360e57abda8fabfafbc23654324a1dfb89efe585c367a0a745aa8474c7b3",
+  "freeze_record_version": "content-region-coverage-v3-freeze-v1",
+  "frozen_at_utc": "2026-08-23T02:55:06.234907+00:00",
+  "pre_score_amendments": [
+    {
+      "amendment_id": "pre-score-amendment-1",
+      "commit": "0e9429d1fe17d9fc4c7f000812272a8e4e59d53f",
+      "finding": "plan A on corpus 480000 failed fail-closed with PROTECTED_CONTENT_CHANGED: the currency protected-span regex consumed preceding horizontal whitespace whenever a double space preceded a currency amount, so an extra space inserted before \"$100\" changed the extracted span text from \"$100\" to \" $100\"",
+      "fix": "currency extraction now requires a sign for the sign-whitespace branch, making span text invariant under preceding whitespace; signed forms still extract; regression tests added; no frozen ruleset or profile hash changed (extractor fix only); the fail-closed plan builder behaved correctly",
+      "kind": "mechanical_correction",
+      "recorded_at_utc": "2026-08-23T04:09:49.020302+00:00"
+    }
+  ],
+  "protocol_id": "content-region-coverage-v3",
+  "protocol_sha256": "ea0de812869d60f7a5cc8e765eb0c5a68db0c61c8722b2347a64752e12fb24a2"
+}
diff --git a/specs/fuckmark-content-region-coverage-v3.protocol.md b/specs/fuckmark-content-region-coverage-v3.protocol.md
new file mode 100644
index 00000000..08df9e41
--- /dev/null
+++ b/specs/fuckmark-content-region-coverage-v3.protocol.md
@@ -0,0 +1,110 @@
+# Frozen Research Protocol: Content-Region Coverage (Cycle 3)
+
+Protocol ID: `content-region-coverage-v3`. Frozen before any Cycle-3 detector scoring.
+Freeze record: `specs/fuckmark-content-region-coverage-v3.freeze.json`.
+
+## 1. Objective and claim boundary
+
+Test whether a general any-word spacing candidate family (a) closes the content-region
+candidate holes diagnosed in Cycles 1-2, (b) beats the Cycle-2 coverage-completion ruleset in
+a paired design on fresh corpora, and (c) holds across three independent confirmation corpora
+under a fixed corpus-independent threshold. Claim boundary unchanged: fixed open HF SynthID
+weighted-mean detector, public development keys, uncleaned text-only path; no removal,
+undetectability, unknown-key, proprietary-detector, or cleaning claims; Level B not pursued.
+
+## 2. Candidate mechanism
+
+Profile `content-region-coverage-v1` (ruleset hash recorded in artifacts): forward
+contractions, the six punctuation spacing rules, ONE new `GeneralWordSpacingRule`
+(`surface-space-after-any-word`, pattern `(?<![A-Za-z])[A-Za-z]+(?= [^ \t\r\n])`, replacement
+= matched word + one space, case-sensitive, word-boundary anchored, no word list), plus the
+existing lexical and syntax rules. Budget 16 operations; COVERAGE_GREEDY_KEY_BLIND over
+public-tokenizer 5-gram geometry; replicate 1; schedule seed base 1_150_000 + sorted source
+index. The Cycle-2 word-list spacing rules are intentionally absent because the general rule
+subsumes them; ablation arm D (dev only) tests the combined ruleset to separate mechanisms.
+Selection uses text and public tokenizer geometry only; no detector information anywhere in
+planning.
+
+## 3. Measurement (Phase A)
+
+`open-detector-measurement-stability-v1`: a dedicated calibration corpus (seed base 500000,
+40 new topics x 4 domains x 8 seeds = 1280 unwatermarked 64-token negatives; 1024 calibration
++ 256 audit by frozen sample-id order) generates the frozen threshold: ascending order
+statistic n - floor(0.01 * n) + 1 = 1015 of 1024 calibration scores; detection score >=
+threshold; float64, no tie rounding. The threshold artifact freezes detector identity,
+corpus hash, counts, realized audit FPR with exact 95% binomial interval, and environment
+identity. ALL Cycle-3 confirmation scoring uses this fixed threshold; per-corpus calibration
+thresholds are recorded alongside for comparison only. Threshold frozen before any
+confirmation score. Dev scoring (both arms on the same corpus) may additionally report
+per-corpus thresholds; paired comparisons use one threshold within each corpus.
+
+## 4. Seed-range ledger (recovered from artifacts)
+
+Consumed: 401000-404296, 410000-414192, 420000-425216, 430000-434192, 440000-445216,
+calibration 500000-520480 (span 160 prompts x 8 slots x stride 16). Cycle 3 uses: dev
+450000 (v3, 8 attack pairs/domain, spans about 450000-454224), confirmations 460000,
+470000, 480000 (v3, 16 attack pairs/domain, each spanning about 5264 seeds). All ranges are
+pairwise disjoint from every consumed range and from each other.
+
+## 5. Development design
+
+Fresh dev corpus 450000 (32 watermarked attack sources). Four plan arms per source, all
+detector-blind before scoring:
+
+A. Cycle-2 coverage-completion ruleset (paired baseline)
+B. Cycle-3 content-region profile
+C. General-spacing-only arm (general rule + punctuation only, no contractions/lexical/syntax)
+D. Combined arm (Cycle-2 word list + general rule)
+
+Primary structural endpoints (no detector data): candidate count, achievable coverage,
+zero-candidate rate, longest uncovered run, uncovered window count, per-source paired
+differences B minus A. Detector outcomes are evaluation-only.
+
+## 6. Promotion gate (all required before any confirmation scoring)
+
+1-8: historical hashes unchanged; suite green except documented environmental failures; hard
+invariants pass on every dev row; protected-span violations 0; introduced hidden/control
+codepoints 0; introduced normalization instability 0; Cf-strip identity holds; no source
+becomes empty or corrupted. 9: B raises achievable coverage materially in the A-low-coverage
+subset (mean paired gain >= 0.05 among the 8 lowest-A-coverage sources). 10: zero-candidate
+rate not above baseline. 11: fidelity metrics not materially regressed (word edit rate,
+protected spans, invariants). 12: paired detector result for B not clearly worse than A on
+dev (detected count difference <= 2 on 32 sources). The confirmation decision (proceed or
+reject) is recorded in the freeze record appendix before confirmation scoring.
+
+## 7. Confirmation design
+
+Three corpora frozen before the first confirmation score (hashes recorded in the appendix
+after generation, before scoring): 460000, 470000, 480000; each 64 watermarked + 64
+unwatermarked attack sources. For each corpus, two frozen plans (A baseline, B candidate)
+built detector-blind, then scored once each with the fixed threshold. Control gates per
+corpus: pristine watermarked >= 60/64 (unconditional denominator primary; conditional count
+reported); transformed unwatermarked == 0/64; fidelity/representation gates 128/128 per arm;
+text-hash overlap 0 against every prior corpus with the pre-registered collision policy:
+any naturally occurring collision is reported and followed by scoring the corpus as
+generated; no regeneration or substitution after seeing outcomes.
+
+## 8. Outcome classes (pre-registered)
+
+STRONG_SUCCESS: all control gates pass on all three corpora AND pooled B residuals strictly
+fewer than pooled A residuals AND B no worse than A on every corpus; stretch target 0/192.
+PARTIAL_SUCCESS: B paired-better overall but residuals remain, or exactly one non-primary
+gate fails. NEUTRAL: B not better than A pooled. REJECTED: B worse, false positives appear,
+fidelity regresses, or the structural hypothesis fails on dev. Post-scoring margin analysis
+(±0.005/±0.010/±0.025 bands) is diagnosis only.
+
+## 9. Fidelity and reporting
+
+All Cycle-1/2 gates retained. For the general-rule family report separately: number of
+spacing insertions, number of sources receiving them, maximum and mean per source, exact
+changed tokens, rule identities; word-level substitutions from other families reported as in
+prior cycles. Blind human fidelity evidence: NOT_PROVIDED (no fabricated judgments).
+
+## 10. Reproducibility
+
+Environment manifest bound in the freeze record (Windows-10-10.0.26220 AMD64, Python
+3.11.15, torch 2.13.0+cpu, transformers 5.16.0.dev0 at the pinned git revision, GPT-2
+revision 607a30d783dfa663caf39e06633721c8d4cfcd7e). Cross-platform corpus generation is NOT
+claimed byte-reproducible (documented Cycle-1 finding); plans, scoring, and thresholds are
+deterministic given texts and the pinned runtime. All artifacts content-addressed; amendments
+only before affected scores, timestamped and hash-bound; local commits only, nothing pushed.
diff --git a/specs/fuckmark-coverage-completion-v2.contract.json b/specs/fuckmark-coverage-completion-v2.contract.json
new file mode 100644
index 00000000..500689f4
--- /dev/null
+++ b/specs/fuckmark-coverage-completion-v2.contract.json
@@ -0,0 +1,136 @@
+{
+  "algorithm_version": "coverage-completion-contract-v2",
+  "base_main_commit": "16e153fdfa3739a88bca9b1559543a10ded2d859",
+  "candidate_profile": {
+    "budget": 16,
+    "budget_justification": "cycle-1 coverage saturation below 16 on every source; no sweep needed",
+    "geometry_mode": "TOKENIZER_AWARE_PUBLIC",
+    "ngram_len": 5,
+    "profile_id": "key-blind-coverage-completion-v2",
+    "replicate_count": 1,
+    "ruleset": "cycle-1 development ruleset plus 65 frozen extension surface words",
+    "schedule_policy": "COVERAGE_GREEDY_KEY_BLIND",
+    "schedule_seed_base": 1140000
+  },
+  "claim_boundary": {
+    "level_b_product_admissible": false,
+    "release_authorized": false,
+    "status": "EXPLORATORY_FIXED_OPEN_DETECTOR_ONLY",
+    "undetectability_claim": false,
+    "watermark_removal_claim": false
+  },
+  "corpora": {
+    "confirmation": {
+      "attack_pairs_per_domain": 16,
+      "profile": "tiny-dev-v3",
+      "seed_base": 440000
+    },
+    "development": [
+      {
+        "attack_pairs_per_domain": 8,
+        "profile": "tiny-dev-v3",
+        "seed_base": 430000
+      },
+      {
+        "attack_pairs_per_domain": 8,
+        "note": "repeat use from cycle 1, labeled",
+        "profile": "tiny-dev-v3",
+        "seed_base": 410000
+      }
+    ],
+    "forbidden": "cycle-1 confirmation corpus at seed base 420000 may not be scored in cycle 2"
+  },
+  "cycle1_reference": {
+    "confirmation_residual_detected": 11,
+    "confirmation_watermarked_sources": 64,
+    "mean_achievable_coverage_all": 0.8187,
+    "mean_achievable_coverage_detected": 0.6818,
+    "mean_achievable_coverage_escaped": 0.8469
+  },
+  "detector": {
+    "comparison_operator": ">=",
+    "family": "Hugging Face SynthID Weighted Mean",
+    "keys": "public development keys",
+    "ngram_len": 5,
+    "target_fpr": 0.01
+  },
+  "endpoints": {
+    "controls": {
+      "gate_pass_fraction_required": 1.0,
+      "pristine_watermarked_detected_min": 60,
+      "transformed_unwatermarked_detected_max": 0
+    },
+    "improvement": "detected count < 11",
+    "mechanistic": "mean achievable coverage >= 0.80 on confirmation watermarked sources",
+    "primary": "confirmation transformed watermarked detected == 0/64"
+  },
+  "extension_words": [
+    "an",
+    "he",
+    "she",
+    "his",
+    "her",
+    "its",
+    "our",
+    "their",
+    "them",
+    "him",
+    "us",
+    "me",
+    "my",
+    "your",
+    "if",
+    "when",
+    "where",
+    "which",
+    "who",
+    "what",
+    "how",
+    "why",
+    "because",
+    "so",
+    "than",
+    "then",
+    "there",
+    "here",
+    "all",
+    "any",
+    "each",
+    "more",
+    "most",
+    "some",
+    "such",
+    "only",
+    "very",
+    "just",
+    "also",
+    "into",
+    "about",
+    "over",
+    "under",
+    "after",
+    "before",
+    "between",
+    "during",
+    "through",
+    "without",
+    "while",
+    "do",
+    "does",
+    "been",
+    "being",
+    "would",
+    "could",
+    "should",
+    "may",
+    "might",
+    "must",
+    "were",
+    "one",
+    "even",
+    "still",
+    "often"
+  ],
+  "protocol_id": "coverage-completion-v2",
+  "recorded_date": "2026-08-23"
+}
diff --git a/specs/fuckmark-coverage-completion-v2.freeze.json b/specs/fuckmark-coverage-completion-v2.freeze.json
new file mode 100644
index 00000000..e06ddbb6
--- /dev/null
+++ b/specs/fuckmark-coverage-completion-v2.freeze.json
@@ -0,0 +1,26 @@
+{
+  "appendix_confirmation_budget": 16,
+  "appendix_development_outcome": {
+    "cycle1_ruleset_paired_baseline_on_430000": 4,
+    "cycle2_dev_detected": {
+      "410000": 0,
+      "430000": 5,
+      "pooled_of_64": 5
+    },
+    "evidence_hashes": {
+      "dev1_paired_baseline_430000": "7c7f9624e2a95dfb16fac5b17dac7778bbe7d87be6af988c2412f09aadb26e9e",
+      "dev2_evidence_410000": "2eda8a0d1c3599e35df38d6779f0ed395e56a13fc958c31f7cf3d689a6b736db",
+      "dev2_evidence_430000": "cf46b933ce3b7ae17a893432d4230db9b7b4f04bae8905844e30f74ad2f9a49a"
+    },
+    "interpretation": "pooled dev detection identical between rulesets (5/64 each); the extension grew candidate pools but residuals concentrate in sources with high pristine scores and content-word-dense low-candidate regions; confirmation proceeds as pre-registered and may return a neutral result",
+    "phase": "development outcome recorded before confirmation scoring",
+    "recorded_at_utc": "2026-08-23T01:39:54.423362+00:00"
+  },
+  "base_main_commit": "16e153fdfa3739a88bca9b1559543a10ded2d859",
+  "contract_sha256": "20ba6145793a89f0aa5cbc530305d9345731a60d60ad906199b323c74942d825",
+  "freeze_record_version": "coverage-completion-v2-freeze-v1",
+  "frozen_at_utc": "2026-08-23T01:24:49.558549+00:00",
+  "pre_score_amendments": [],
+  "protocol_id": "coverage-completion-v2",
+  "protocol_sha256": "65856295a595acaa404392239ccd9db9fa43d3f45a86ae61ee0d88b0d1e0851a"
+}
diff --git a/specs/fuckmark-coverage-completion-v2.protocol.md b/specs/fuckmark-coverage-completion-v2.protocol.md
new file mode 100644
index 00000000..142c1cd0
--- /dev/null
+++ b/specs/fuckmark-coverage-completion-v2.protocol.md
@@ -0,0 +1,85 @@
+# Frozen Research Protocol: Key-Blind Coverage Completion (v2)
+
+Protocol ID: `coverage-completion-v2`
+Cycle 2 of the budget-scaled effectiveness line. Frozen before any cycle-2 scoring. Hash-binding
+freeze record: `specs/fuckmark-coverage-completion-v2.freeze.json`.
+
+## 1. Objective and claim boundary
+
+Level A: for the same fixed open detector and uncleaned text-only input path as cycle 1, test
+whether a coverage-completion ruleset - the cycle-1 development ruleset plus an extended
+surface spacing word list chosen from standard general-English function words - lowers
+watermarked held-out detection on a new source-disjoint 64-source confirmation corpus relative
+to cycle 1's 11/64 residual, with stretch target 0/64. Mechanistic endpoint: mean achievable
+detector-n-gram coverage of the confirmation watermarked sources must be at least 0.80 (cycle 1
+measured 0.819 overall with 0.682 among residual sources). The claim boundary is identical to
+cycle 1: detector-specific detection reduction under the documented fixed condition only; no
+removal, undetectability, unknown-key, proprietary-detector, cleaning-durability, or release
+claims. Level B is not pursued; the candidate edits visible text.
+
+## 2. Candidate mechanism
+
+Profile `key-blind-coverage-completion-v2`: the cycle-1 registry (forward contractions, surface
+spacing, lexical, syntax) EXTENDED by 65 additional surface spacing words, frozen below;
+COVERAGE_GREEDY_KEY_BLIND scheduling over public-tokenizer n-gram disruption geometry
+(ngram_len 5); replicate count 1; schedule seed base 1_140_000 plus sorted source index;
+budget fixed at 16 operations (cycle 1 demonstrated coverage saturation below 16 on every
+source, so a budget sweep carries no information; this is pre-registered, not tuned).
+Selection accesses only public tokenizer geometry and the public detector n-gram length.
+
+Frozen extension words (65, lowercase alphabetic, length >= 2, none already in the cycle-1
+surface list, chosen from standard general-English function-word rankings, not mined from any
+project corpus):
+
+an, he, she, his, her, its, our, their, them, him, us, me, my, your, if, when, where, which,
+who, what, how, why, because, so, than, then, there, here, all, any, each, more, most, some,
+such, only, very, just, also, into, about, over, under, after, before, between, during,
+through, without, while, do, does, been, being, would, could, should, may, might, must, were,
+one, even, still, often
+
+## 3. Data splits and source disjointness
+
+- Development: fresh corpus at seed base 430000 (v3, 8 attack pairs per domain, 32 watermarked
+  attack sources) plus the cycle-1 development corpus at seed base 410000 (repeat use,
+  labeled; overfitting caveat noted) and the locally regenerated 401000 corpus. No cycle-2
+  scoring may read the cycle-1 confirmation corpus at 420000.
+- Confirmation: fresh corpus at seed base 440000 (v3, 16 attack pairs per domain, 64
+  watermarked attack sources plus 64 unwatermarked controls), generated after this protocol is
+  frozen and scored exactly once.
+- Disjointness: pairwise text-hash overlap zero across 410000, 430000, and 440000 corpora;
+  degenerate-generation collisions (cycle 1 recorded one against 401000) are checked and
+  reported; any collision is a reportable deviation.
+
+## 4. Generation and detector configuration
+
+Identical to cycle 1 (pinned GPT-2 revision, CPU, temperature 0.8, top-k 50, top-p 0.95,
+64 tokens, 16 attempts; HF SynthID weighted mean, ngram_len 5, public development keys,
+per-corpus text-only calibration at target FPR 0.01, decision score >= threshold).
+
+## 5. Controls, gates, robustness
+
+All four paired controls scored. All cycle-1 section-6 gates apply unchanged (hard invariants,
+protected spans zero, word edit rate <= 0.30, no introduced non-ASCII or hidden-category
+codepoints, no introduced normalization instability, Cf-strip identity on introduced
+characters, fixed-browser DOM text equality with archived screenshot).
+
+## 6. Pre-registered endpoints and success criteria
+
+Primary: confirmation transformed-watermarked detected count, target 0/64.
+Improvement criterion (secondary, must hold for the cycle to count as progress): detected
+count strictly below 11 (cycle 1 residual on an equally constructed corpus).
+Mechanistic criterion: mean achievable coverage >= 0.80 on confirmation watermarked sources.
+Control criteria: pristine watermarked >= 60/64 detected; transformed unwatermarked == 0/64;
+all fidelity gates pass on 100% of rows.
+Adverse results (residual detection, any gate failure, any cross-corpus text collision,
+pristine-unwatermarked exceedances, zero-candidate sources) are reportable, never hidden.
+The frozen budget (16) is recorded in the freeze-record appendix before confirmation scoring;
+no post-hoc change.
+
+## 7. Reproducibility
+
+Canonical JSON artifacts with SHA-256 hashes; plan binds corpus, manifest, code commit, and
+explicit detector_access_observed=False / secret_access_observed=False; evidence binds plan,
+profile, ruleset, detector identity, calibration bundle, threshold; robustness report binds
+plans and corpora; rendering manifest binds the plan; independent hash cross-check at the end;
+full test suite, `git diff --check`, and clean status; local commits only, no pushes.
diff --git a/tests/test_budget_scaled_robustness.py b/tests/test_budget_scaled_robustness.py
new file mode 100644
index 00000000..8d6b3675
--- /dev/null
+++ b/tests/test_budget_scaled_robustness.py
@@ -0,0 +1,168 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+from fuckmark.corpus import CorpusDomain, CorpusSplit, WatermarkLabel
+from fuckmark.experiments.effectiveness_plan import build_key_blind_high_coverage_plan
+from fuckmark.hashing import sha256_text
+from fuckmark.tiny_dev_budget_scaled_robustness import (
+    _cf_stripped,
+    _forbidden_codepoints,
+    build_budget_scaled_robustness_report,
+)
+from fuckmark.transforms import key_blind_full_pool_coverage_profile
+
+
+class FakeTokenizer:
+    def __call__(
+        self,
+        text: str,
+        *,
+        add_special_tokens: bool,
+        return_offsets_mapping: bool = False,
+    ) -> dict[str, object]:
+        assert add_special_tokens is False
+        ids = [index + 1 for index in range(len(text))]
+        value: dict[str, object] = {"input_ids": ids}
+        if return_offsets_mapping:
+            value["offset_mapping"] = [(index, index + 1) for index in range(len(text))]
+        return value
+
+
+def _sample(sample_id: str, label: WatermarkLabel, text: str, identity_hash: str):
+    token_ids = tuple(index + 1 for index in range(len(text)))
+    return SimpleNamespace(
+        sample_id=sample_id,
+        split=CorpusSplit.ATTACK_DEVELOPMENT,
+        label=label,
+        prompt_family_id=f"prompt-{sample_id}",
+        domain=CorpusDomain.GENERAL_EXPLANATORY,
+        text=text,
+        text_sha256=sha256_text(text),
+        text_only_tokens=SimpleNamespace(token_ids=token_ids),
+        model=SimpleNamespace(identity_hash=identity_hash, eos_token_id=50256),
+    )
+
+
+def _corpus(text: str, salt: str):
+    identity_hash = sha256_text("fake-tokenizer")
+    samples = (
+        _sample(f"negative-{salt}", WatermarkLabel.UNWATERMARKED, text, identity_hash),
+        _sample(f"positive-{salt}", WatermarkLabel.WATERMARKED, text, identity_hash),
+    )
+    return SimpleNamespace(
+        artifact_hash=sha256_text(f"fake-corpus-{salt}"),
+        model_identity_hash=identity_hash,
+        manifest=SimpleNamespace(samples=samples, manifest_hash=sha256_text("fake-manifest")),
+    )
+
+
+def test_forbidden_codepoint_audit_detects_hidden_representation() -> None:
+    clean = "plain ascii text with spaces only"
+    assert _forbidden_codepoints(clean) == ()
+    zero_width = "hidden" + chr(0x200C) + "join"
+    combining = "combining" + chr(0x0301)
+    nbsp = "nbsp" + chr(0x00A0)
+    soft_hyphen = "soft" + chr(0x00AD)
+    assert _forbidden_codepoints(zero_width) == ("U+200C(Cf)",)
+    assert _forbidden_codepoints(combining) == ("U+0301(Mn)",)
+    assert _forbidden_codepoints(nbsp) == ("U+00A0(Zs)",)
+    assert _forbidden_codepoints(soft_hyphen) == ("U+00AD(Cf)",)
+    assert _cf_stripped(zero_width) == "hiddenjoin"
+    assert _cf_stripped(clean) == clean
+
+
+def test_introduced_codepoint_gate_ignores_preexisting_source_characters() -> None:
+    from fuckmark.tiny_dev_budget_scaled_robustness import (
+        _introduced_forbidden_codepoints,
+        _introduced_non_ascii,
+        _robustness_row,
+    )
+
+    source = "source with\nnewline and " + chr(0x2019) + "curly quote"
+    transformed_same = source + " and one more plain ascii word"
+    assert _introduced_forbidden_codepoints(source, transformed_same) == ()
+    assert _introduced_non_ascii(source, transformed_same) == ()
+    transformed_hidden = transformed_same + chr(0x200B)
+    assert _introduced_forbidden_codepoints(source, transformed_hidden) == ("U+200B(Cf)",)
+    transformed_visible_unicode = transformed_same + chr(0x00E9)
+    assert _introduced_non_ascii(source, transformed_visible_unicode) == ("U+00E9",)
+
+
+def test_normalization_gate_ignores_source_instability_but_flags_introduced_instability() -> None:
+    from fuckmark.tiny_dev_budget_scaled_robustness import _robustness_row
+
+    stable_source = "plain stable ascii source text"
+    stable_row = _robustness_row(stable_source, stable_source + " edited")
+    assert stable_row["gates_pass"] is True
+    assert stable_row["introduced_normalization_instability"] == ()
+    decomposed_source = "caf" + chr(0x0065) + chr(0x0301) + " source text with several more words here"
+    inherited_decomposed = _robustness_row(decomposed_source, decomposed_source + " edited")
+    assert inherited_decomposed["normalization_noops"]["nfc"] is False
+    assert inherited_decomposed["introduced_normalization_instability"] == ()
+    assert inherited_decomposed["gates_pass"] is True
+    introduced_unstable = _robustness_row(stable_source, stable_source + " caf" + chr(0x0065) + chr(0x0301))
+    assert introduced_unstable["introduced_normalization_instability"] == ("nfc", "nfkc")
+    assert introduced_unstable["gates_pass"] is False
+    unstable_source = "caf" + chr(0x00E9) + " source text with several more words here"
+    inherited_row = _robustness_row(unstable_source, unstable_source + " edited")
+    assert inherited_row["normalization_noops"]["nfd"] is False
+    assert inherited_row["introduced_normalization_instability"] == ()
+    assert inherited_row["gates_pass"] is True
+
+
+def test_robustness_report_gates_pass_on_rule_transforms() -> None:
+    text = "You are not ready, and we do not stop when the system is in use."
+    corpus = _corpus(text, "1")
+    plan = build_key_blind_high_coverage_plan(
+        corpus,
+        FakeTokenizer(),
+        profile=key_blind_full_pool_coverage_profile((32,)),
+        source_code_commit="a" * 40,
+    )
+    report = build_budget_scaled_robustness_report((corpus,), (plan,))
+    assert report["summary"]["row_count"] == 2
+    assert report["summary"]["gate_pass_fraction"] == 1.0
+    assert report["summary"]["all_normalization_stability_preserved"] is True
+    assert report["summary"]["all_cf_strip_noop"] is True
+    assert report["summary"]["all_introduced_codepoints_clean"] is True
+    assert report["summary"]["corpus_pairwise_text_hash_overlaps"] == {}
+    assert all(row["gates_pass"] for row in report["rows"])
+    assert report["artifact_hash"]
+
+
+def test_robustness_report_joins_plans_to_their_own_corpus_by_artifact_hash() -> None:
+    identity_hash = sha256_text("fake-tokenizer")
+    first_text = "You are not ready, and we do not stop when the system is in use."
+    second_text = "A second corpus shares sample IDs but holds different source texts here."
+    first = _corpus(first_text, "1")
+    second = _corpus(second_text, "1")
+    first.artifact_hash = sha256_text("corpus-a")
+    second.artifact_hash = sha256_text("corpus-b")
+    for corpus, text in ((first, first_text), (second, second_text)):
+        for sample in corpus.manifest.samples:
+            sample.text = text
+            sample.text_sha256 = sha256_text(text)
+    plan = build_key_blind_high_coverage_plan(
+        first,
+        FakeTokenizer(),
+        profile=key_blind_full_pool_coverage_profile((16,)),
+        source_code_commit="a" * 40,
+    )
+    report = build_budget_scaled_robustness_report((first, second), (plan,))
+    assert all(row["corpus_artifact_hash"] == sha256_text("corpus-a") for row in report["rows"])
+    assert report["summary"]["gate_pass_fraction"] == 1.0
+
+
+def test_robustness_report_detects_cross_corpus_text_overlap() -> None:
+    text = "Shared generation text that appears in two corpora at once."
+    first = _corpus(text, "1")
+    second = _corpus(text, "2")
+    plan = build_key_blind_high_coverage_plan(
+        first,
+        FakeTokenizer(),
+        profile=key_blind_full_pool_coverage_profile((16,)),
+        source_code_commit="a" * 40,
+    )
+    report = build_budget_scaled_robustness_report((first, second), (plan,))
+    assert report["summary"]["corpus_pairwise_text_hash_overlaps"] == {"0-1": 1}
diff --git a/tests/test_content_region_profile.py b/tests/test_content_region_profile.py
new file mode 100644
index 00000000..1c7fa221
--- /dev/null
+++ b/tests/test_content_region_profile.py
@@ -0,0 +1,154 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+
+from fuckmark.corpus import CorpusDomain, CorpusSplit, WatermarkLabel
+from fuckmark.experiments.coverage_holes import classify_word
+from fuckmark.experiments.effectiveness_plan import build_key_blind_high_coverage_plan
+from fuckmark.hashing import sha256_text
+from fuckmark.transforms import (
+    CONTENT_REGION_COVERAGE_PROFILE_ID,
+    CONTENT_REGION_COVERAGE_SEED_BASE,
+    KEY_BLIND_HIGH_COVERAGE_PROFILE,
+    content_region_coverage_profile,
+    content_region_coverage_transform_registry,
+    resolve_effectiveness_profile,
+)
+from fuckmark.transforms.rules import GeneralWordSpacingRule
+
+
+class FakeTokenizer:
+    def __call__(
+        self,
+        text: str,
+        *,
+        add_special_tokens: bool,
+        return_offsets_mapping: bool = False,
+    ) -> dict[str, object]:
+        assert add_special_tokens is False
+        ids = [index + 1 for index in range(len(text))]
+        value: dict[str, object] = {"input_ids": ids}
+        if return_offsets_mapping:
+            value["offset_mapping"] = [(index, index + 1) for index in range(len(text))]
+        return value
+
+
+def _sample(sample_id: str, label: WatermarkLabel, text: str, identity_hash: str):
+    token_ids = tuple(index + 1 for index in range(len(text)))
+    return SimpleNamespace(
+        sample_id=sample_id,
+        split=CorpusSplit.ATTACK_DEVELOPMENT,
+        label=label,
+        prompt_family_id=f"prompt-{sample_id}",
+        domain=CorpusDomain.GENERAL_EXPLANATORY,
+        text=text,
+        text_sha256=sha256_text(text),
+        text_only_tokens=SimpleNamespace(token_ids=token_ids),
+        model=SimpleNamespace(identity_hash=identity_hash, eos_token_id=50256),
+    )
+
+
+def _corpus():
+    identity_hash = sha256_text("fake-tokenizer")
+    text = (
+        "Careful researchers documented measurement uncertainty thoroughly. "
+        "The auditor verified every reported number 42 before publishing results."
+    )
+    samples = (
+        _sample("negative-1", WatermarkLabel.UNWATERMARKED, text, identity_hash),
+        _sample("positive-1", WatermarkLabel.WATERMARKED, text, identity_hash),
+    )
+    return SimpleNamespace(
+        artifact_hash=sha256_text("fake-corpus"),
+        model_identity_hash=identity_hash,
+        manifest=SimpleNamespace(samples=samples, manifest_hash=sha256_text("fake-manifest")),
+    )
+
+
+def test_general_word_spacing_rule_contract() -> None:
+    rule = GeneralWordSpacingRule.create("surface-space-after-any-word")
+    text = "Alpha beta gamma delta, epsilon zeta."
+    matches = [text[m.start() : m.end()] for m in rule.pattern().finditer(text)]
+    assert "Alpha" in matches
+    assert "beta" in matches
+    assert "gamma" in matches
+    assert "delta" not in matches
+    assert rule.replacement_for("beta") == "beta "
+    assert rule.replacement_for("Beta") == "Beta "
+    doubled = "beta  gamma"
+    assert rule.pattern().search(doubled) is None
+    with pytest.raises(ValueError):
+        GeneralWordSpacingRule(
+            rule_id="bad",
+            version="general-word-space-after-v1",
+            family=rule.family,
+            tier=rule.tier,
+            source="word",
+            replacement="wrong ",
+            whole_word=False,
+            preserve_simple_case=False,
+            block_all_caps=False,
+            rule_hash=rule.rule_hash,
+        )
+
+
+def test_general_rule_enumerates_content_words_with_exact_replacement() -> None:
+    registry = content_region_coverage_transform_registry()
+    text = "Measurement uncertainty remained stubbornly high throughout replication attempts."
+    enumeration = registry.enumerate(text)
+    general = [
+        candidate
+        for candidate in enumeration.candidates
+        if candidate.rule_id == "surface-space-after-any-word"
+    ]
+    assert any(candidate.source_text == "Measurement" for candidate in general)
+    assert all(candidate.replacement_text == candidate.source_text + " " for candidate in general)
+    for candidate in general:
+        transformed = text[: candidate.start] + candidate.replacement_text + text[candidate.end :]
+        assert transformed.count(candidate.source_text + "  ") >= 1
+        assert transformed.isascii()
+
+
+def test_content_region_profile_resolves_and_builds_detector_blind_plans() -> None:
+    profile = resolve_effectiveness_profile(CONTENT_REGION_COVERAGE_PROFILE_ID, (16,))
+    assert profile.profile_id == CONTENT_REGION_COVERAGE_PROFILE_ID
+    assert profile.schedule_seed_base == CONTENT_REGION_COVERAGE_SEED_BASE
+    assert content_region_coverage_profile((16,)) == profile
+    corpus = _corpus()
+    plan = build_key_blind_high_coverage_plan(
+        corpus,
+        FakeTokenizer(),
+        profile=profile,
+        source_code_commit="a" * 40,
+    )
+    assert plan["ruleset_hash"] == profile.ruleset_hash
+    assert all(row["hard_invariant_status"] == "pass" for row in plan["variants"])
+    assert all(row["detector_access_observed"] is False for row in plan["variants"])
+
+
+def test_content_region_registry_protects_numbers_and_keeps_b16_frozen() -> None:
+    registry = content_region_coverage_transform_registry()
+    text = "The reported value 3.14159 stayed fixed across runs."
+    enumeration = registry.enumerate(text)
+    for candidate in enumeration.candidates:
+        assert "3.14159" not in candidate.source_text
+    assert KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_hash == (
+        "6ad142262bfb11a714565d7bd43daa859657fe817bdafa9c8dcf0f4884c07512"
+    )
+
+
+def test_classify_word_categories() -> None:
+    assert classify_word("the") == "function_word"
+    assert classify_word("measurement") == "lowercase_content"
+    assert classify_word("Measurement") == "capitalized_content"
+    assert classify_word("42") == "numeric"
+    assert classify_word(",") == "punctuation_or_empty"
+
+
+def test_resolve_rejects_invalid_content_region_requests() -> None:
+    with pytest.raises(ValueError):
+        resolve_effectiveness_profile(CONTENT_REGION_COVERAGE_PROFILE_ID)
+    with pytest.raises(ValueError):
+        content_region_coverage_profile((48, 16))
diff --git a/tests/test_coverage_completion_profile.py b/tests/test_coverage_completion_profile.py
new file mode 100644
index 00000000..fc55a725
--- /dev/null
+++ b/tests/test_coverage_completion_profile.py
@@ -0,0 +1,139 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+
+from fuckmark.corpus import CorpusDomain, CorpusSplit, WatermarkLabel
+from fuckmark.experiments.effectiveness_plan import build_key_blind_high_coverage_plan
+from fuckmark.hashing import sha256_text
+from fuckmark.transforms import (
+    KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID,
+    KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE,
+    KEY_BLIND_HIGH_COVERAGE_PROFILE,
+    key_blind_coverage_completion_profile,
+    key_blind_coverage_completion_transform_registry,
+    key_blind_high_coverage_transform_registry,
+    resolve_effectiveness_profile,
+)
+from fuckmark.transforms.surface_rules import (
+    coverage_completion_extension_words,
+    coverage_completion_surface_rules,
+    development_surface_rules,
+)
+
+
+class FakeTokenizer:
+    def __call__(
+        self,
+        text: str,
+        *,
+        add_special_tokens: bool,
+        return_offsets_mapping: bool = False,
+    ) -> dict[str, object]:
+        assert add_special_tokens is False
+        ids = [index + 1 for index in range(len(text))]
+        value: dict[str, object] = {"input_ids": ids}
+        if return_offsets_mapping:
+            value["offset_mapping"] = [(index, index + 1) for index in range(len(text))]
+        return value
+
+
+def _sample(sample_id: str, label: WatermarkLabel, text: str, identity_hash: str):
+    token_ids = tuple(index + 1 for index in range(len(text)))
+    return SimpleNamespace(
+        sample_id=sample_id,
+        split=CorpusSplit.ATTACK_DEVELOPMENT,
+        label=label,
+        prompt_family_id=f"prompt-{sample_id}",
+        domain=CorpusDomain.GENERAL_EXPLANATORY,
+        text=text,
+        text_sha256=sha256_text(text),
+        text_only_tokens=SimpleNamespace(token_ids=token_ids),
+        model=SimpleNamespace(identity_hash=identity_hash, eos_token_id=50256),
+    )
+
+
+def _corpus():
+    identity_hash = sha256_text("fake-tokenizer")
+    text = "He said they were not sure, because more work was needed before one can decide."
+    samples = (
+        _sample("negative-1", WatermarkLabel.UNWATERMARKED, text, identity_hash),
+        _sample("positive-1", WatermarkLabel.WATERMARKED, text, identity_hash),
+    )
+    return SimpleNamespace(
+        artifact_hash=sha256_text("fake-corpus"),
+        model_identity_hash=identity_hash,
+        manifest=SimpleNamespace(samples=samples, manifest_hash=sha256_text("fake-manifest")),
+    )
+
+
+def test_extension_words_obey_the_frozen_surface_contract() -> None:
+    words = coverage_completion_extension_words()
+    assert len(words) == 65
+    assert len(set(words)) == len(words)
+    base_words = {rule.source for rule in development_surface_rules() if rule.source.isalpha()}
+    assert not (set(words) & base_words)
+    assert all(word.isalpha() and word == word.lower() and len(word) >= 2 for word in words)
+    rules = coverage_completion_surface_rules()
+    base = development_surface_rules()
+    assert len(rules) == len(base) + 65
+    assert set(rule.rule_id for rule in base) < set(rule.rule_id for rule in rules)
+
+
+def test_extension_rules_do_not_split_words_mid_token() -> None:
+    registry = key_blind_coverage_completion_transform_registry()
+    text = "The weather, whether he measured then, was often more random than before."
+    enumeration = registry.enumerate(text)
+    replaced_words = set()
+    for candidate in enumeration.candidates:
+        replaced_words.add(text[candidate.start : candidate.end].strip())
+    assert "he" in replaced_words or "then" in replaced_words
+    joined = "".join(
+        candidate.replacement_text
+        for candidate in enumeration.candidates[:1]
+    )
+    assert "random" not in joined or joined == "random"
+    transformed_spans = [text[c.start : c.end] for c in enumeration.candidates]
+    assert all(span.strip().isalpha() or span in (". ", ", ", "; ", ": ", "? ", "! ") for span in transformed_spans)
+
+
+def test_coverage_completion_registry_extends_and_rebinds_ruleset() -> None:
+    base_registry = key_blind_high_coverage_transform_registry()
+    registry = key_blind_coverage_completion_transform_registry()
+    assert registry.ruleset_hash != base_registry.ruleset_hash
+    base_ids = {rule.rule_id for rule in base_registry.rules}
+    extended_ids = {rule.rule_id for rule in registry.rules}
+    assert base_ids < extended_ids
+
+
+def test_frozen_b16_profile_hash_is_unchanged() -> None:
+    assert (
+        KEY_BLIND_HIGH_COVERAGE_PROFILE.profile_hash
+        == "6ad142262bfb11a714565d7bd43daa859657fe817bdafa9c8dcf0f4884c07512"
+    )
+
+
+def test_coverage_completion_profile_resolves_and_builds_plans() -> None:
+    profile = resolve_effectiveness_profile(KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID, (16,))
+    assert profile.profile_id == KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID
+    assert profile.schedule_seed_base == KEY_BLIND_COVERAGE_COMPLETION_SEED_BASE
+    assert key_blind_coverage_completion_profile((16,)) == profile
+    corpus = _corpus()
+    plan = build_key_blind_high_coverage_plan(
+        corpus,
+        FakeTokenizer(),
+        profile=profile,
+        source_code_commit="a" * 40,
+    )
+    assert plan["ruleset_hash"] == profile.ruleset_hash
+    assert len(plan["variants"]) == 2
+    assert all(row["hard_invariant_status"] == "pass" for row in plan["variants"])
+    assert all(row["detector_access_observed"] is False for row in plan["variants"])
+
+
+def test_resolve_rejects_invalid_coverage_completion_requests() -> None:
+    with pytest.raises(ValueError):
+        resolve_effectiveness_profile(KEY_BLIND_COVERAGE_COMPLETION_PROFILE_ID)
+    with pytest.raises(ValueError):
+        key_blind_coverage_completion_profile((48, 16))
diff --git a/tests/test_effectiveness_full_pool_profile.py b/tests/test_effectiveness_full_pool_profile.py
new file mode 100644
index 00000000..a3fa96c9
--- /dev/null
+++ b/tests/test_effectiveness_full_pool_profile.py
@@ -0,0 +1,152 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+
+from fuckmark.corpus import CorpusDomain, CorpusSplit, WatermarkLabel
+from fuckmark.experiments.effectiveness_plan import (
+    build_key_blind_high_coverage_plan,
+    validate_key_blind_high_coverage_plan,
+)
+from fuckmark.hashing import sha256_text
+from fuckmark.transforms import (
+    KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID,
+    KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE,
+    KEY_BLIND_HIGH_COVERAGE_PROFILE_ID,
+    key_blind_full_pool_coverage_profile,
+    resolve_effectiveness_profile,
+)
+from fuckmark.tiny_dev_effectiveness_plan_hf import _parse_budgets
+from fuckmark.tiny_dev_effectiveness_score_hf import _parse_budgets as _parse_budgets_score
+
+
+class FakeTokenizer:
+    def __call__(
+        self,
+        text: str,
+        *,
+        add_special_tokens: bool,
+        return_offsets_mapping: bool = False,
+    ) -> dict[str, object]:
+        assert add_special_tokens is False
+        ids = [index + 1 for index in range(len(text))]
+        value: dict[str, object] = {"input_ids": ids}
+        if return_offsets_mapping:
+            value["offset_mapping"] = [(index, index + 1) for index in range(len(text))]
+        return value
+
+
+def _sample(sample_id: str, label: WatermarkLabel, text: str, identity_hash: str):
+    token_ids = tuple(index + 1 for index in range(len(text)))
+    return SimpleNamespace(
+        sample_id=sample_id,
+        split=CorpusSplit.ATTACK_DEVELOPMENT,
+        label=label,
+        prompt_family_id=f"prompt-{sample_id}",
+        domain=CorpusDomain.GENERAL_EXPLANATORY,
+        text=text,
+        text_sha256=sha256_text(text),
+        text_only_tokens=SimpleNamespace(token_ids=token_ids),
+        model=SimpleNamespace(identity_hash=identity_hash, eos_token_id=50256),
+    )
+
+
+def _corpus():
+    identity_hash = sha256_text("fake-tokenizer")
+    text = "You are not ready, and we do not stop when the system is in use."
+    samples = (
+        _sample("negative-1", WatermarkLabel.UNWATERMARKED, text, identity_hash),
+        _sample("positive-1", WatermarkLabel.WATERMARKED, text, identity_hash),
+    )
+    return SimpleNamespace(
+        artifact_hash=sha256_text("fake-corpus"),
+        model_identity_hash=identity_hash,
+        manifest=SimpleNamespace(samples=samples, manifest_hash=sha256_text("fake-manifest")),
+    )
+
+
+def test_full_pool_profile_is_deterministic_and_binds_budgets() -> None:
+    first = key_blind_full_pool_coverage_profile((16, 24, 32, 48))
+    second = key_blind_full_pool_coverage_profile((16, 24, 32, 48))
+    assert first == second
+    assert first.profile_id == KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID
+    assert first.budgets == (16, 24, 32, 48)
+    assert first.schedule_seed_base == KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE
+    assert first.ruleset_hash == resolve_effectiveness_profile(
+        KEY_BLIND_HIGH_COVERAGE_PROFILE_ID
+    ).ruleset_hash
+    other = key_blind_full_pool_coverage_profile((32,))
+    assert other.profile_hash != first.profile_hash
+
+
+def test_resolve_effectiveness_profile_rejects_invalid_requests() -> None:
+    with pytest.raises(ValueError):
+        resolve_effectiveness_profile("unknown-profile")
+    with pytest.raises(ValueError):
+        resolve_effectiveness_profile(KEY_BLIND_HIGH_COVERAGE_PROFILE_ID, (16,))
+    with pytest.raises(ValueError):
+        resolve_effectiveness_profile(KEY_BLIND_FULL_POOL_COVERAGE_PROFILE_ID)
+    with pytest.raises(ValueError):
+        key_blind_full_pool_coverage_profile((48, 16))
+
+
+def test_full_pool_plan_covers_every_budget_with_derived_seeds() -> None:
+    corpus = _corpus()
+    profile = key_blind_full_pool_coverage_profile((24, 32))
+    plan = build_key_blind_high_coverage_plan(
+        corpus,
+        FakeTokenizer(),
+        profile=profile,
+        source_code_commit="a" * 40,
+    )
+    validate_key_blind_high_coverage_plan(plan, corpus, profile)
+    assert plan["budgets"] == (24, 32)
+    assert len(plan["variants"]) == 4
+    assert {row["requested_budget"] for row in plan["variants"]} == {24, 32}
+    assert [row["schedule_seed"] for row in plan["variants"]] == [
+        KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE,
+        KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE,
+        KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE + 1,
+        KEY_BLIND_FULL_POOL_COVERAGE_SEED_BASE + 1,
+    ]
+    assert all(row["detector_access_observed"] is False for row in plan["variants"])
+    assert all(row["secret_access_observed"] is False for row in plan["variants"])
+
+
+def test_full_pool_plan_rejects_mismatched_profile_on_validation() -> None:
+    corpus = _corpus()
+    profile = key_blind_full_pool_coverage_profile((24,))
+    plan = build_key_blind_high_coverage_plan(
+        corpus,
+        FakeTokenizer(),
+        profile=profile,
+        source_code_commit="a" * 40,
+    )
+    with pytest.raises(ValueError):
+        validate_key_blind_high_coverage_plan(
+            plan,
+            corpus,
+            key_blind_full_pool_coverage_profile((32,)),
+        )
+
+
+@pytest.mark.parametrize(
+    ("raw", "expected"),
+    (
+        ("", ()),
+        ("16", (16,)),
+        ("16,24,32,48", (16, 24, 32, 48)),
+    ),
+)
+def test_budget_parsing_accepts_valid_lists(raw: str, expected: tuple[int, ...]) -> None:
+    assert _parse_budgets(raw) == expected
+    assert _parse_budgets_score(raw) == expected
+
+
+@pytest.mark.parametrize("raw", ("16,,24", "0", "-4", "24,16", "16,16"))
+def test_budget_parsing_rejects_invalid_lists(raw: str) -> None:
+    with pytest.raises(ValueError):
+        _parse_budgets(raw)
+    with pytest.raises(ValueError):
+        _parse_budgets_score(raw)
diff --git a/tests/test_measurement_calibration.py b/tests/test_measurement_calibration.py
new file mode 100644
index 00000000..db1719e4
--- /dev/null
+++ b/tests/test_measurement_calibration.py
@@ -0,0 +1,135 @@
+from __future__ import annotations
+
+import pytest
+
+from fuckmark.config import canonical_json_text
+from fuckmark.corpus import (
+    CorpusDomain,
+    CorpusSplit,
+    GenerationParameters,
+    KeySplit,
+    ModelTokenizerIdentity,
+    PaddingSide,
+    WatermarkCondition,
+    WatermarkLabel,
+)
+from fuckmark.corpus.measurement_calibration import (
+    MEASUREMENT_CALIBRATION_AUDIT_COUNT,
+    MEASUREMENT_CALIBRATION_NEGATIVE_COUNT,
+    MEASUREMENT_CALIBRATION_SAMPLE_COUNT,
+    build_measurement_calibration_corpus,
+)
+from fuckmark.corpus.tiny_dev_generation import (
+    TINY_DEV_SEED_POLICY_ID,
+    TinyDevGeneratedContinuation,
+)
+from fuckmark.hashing import sha256_json, sha256_text
+from fuckmark.tiny_dev_measurement_calibration_hf import (
+    build_measurement_calibration_prompt_records,
+    build_real_measurement_calibration_corpus,
+)
+
+
+class FakeCalibrationBackend:
+    def __init__(self) -> None:
+        self._model = ModelTokenizerIdentity.create(
+            model_id="example/calibration-model",
+            model_revision="a" * 40,
+            tokenizer_id="example/calibration-tokenizer",
+            tokenizer_revision="b" * 40,
+            chat_template_present=False,
+            chat_template_hash=sha256_text(""),
+            special_token_map_hash=sha256_json({"eos_token": "<eos>", "pad_token": "<pad>"}),
+            padding_side=PaddingSide.LEFT,
+            bos_token_id=None,
+            eos_token_id=2,
+            pad_token_id=0,
+            add_bos_token=False,
+            add_eos_token=False,
+        )
+        self._watermark = WatermarkCondition.create(
+            sha256_json({"ngram_len": 5, "keys": (1, 2, 3)}),
+            KeySplit.DEV,
+            "dev-test-key",
+        )
+
+    @property
+    def model_identity(self) -> ModelTokenizerIdentity:
+        return self._model
+
+    @property
+    def watermark_condition(self) -> WatermarkCondition:
+        return self._watermark
+
+    def generation_parameters(self, seed: int) -> GenerationParameters:
+        return GenerationParameters.create(
+            seed=seed,
+            seed_policy_id=TINY_DEV_SEED_POLICY_ID,
+            temperature=0.8,
+            top_k=50,
+            top_p=0.95,
+            max_new_tokens=64,
+            do_sample=True,
+            dtype="float32",
+            device="cpu",
+            backend_id="fake-calibration",
+            backend_version="1",
+        )
+
+    def generate(self, prompt: str, seed: int, *, watermarked: bool) -> TinyDevGeneratedContinuation:
+        assert watermarked is False
+        prompt_token = 10 + (sum(prompt.encode("utf-8")) % 1000)
+        continuation = tuple(
+            200_000 + ((seed * 977 + index) % 90_000)
+            for index in range(64)
+        )
+        text = f"calibration negative for {sha256_text(prompt)[:12]} seed {seed}"
+        text_only = tuple(300_000 + ((seed * 31 + index) % 80_000) for index in range(16))
+        return TinyDevGeneratedContinuation(
+            text=text,
+            input_token_ids=(prompt_token, prompt_token + 1),
+            attention_mask=(1, 1),
+            continuation_token_ids=continuation,
+            text_only_token_ids=text_only,
+        )
+
+
+def test_measurement_calibration_prompt_records_are_frozen_and_disjoint() -> None:
+    prompts = build_measurement_calibration_prompt_records()
+    assert len(prompts) == 160
+    assert len({prompt.prompt_id for prompt in prompts}) == 160
+    counts: dict[CorpusDomain, int] = {}
+    for prompt in prompts:
+        counts[prompt.domain] = counts.get(prompt.domain, 0) + 1
+    assert set(counts.values()) == {40}
+    from fuckmark.corpus.tiny_dev_v3_generation import build_tiny_dev_v3_prompt_records
+
+    prior_texts = {
+        prompt.text
+        for prompt in build_tiny_dev_v3_prompt_records(16)
+    }
+    assert not any(prompt.text in prior_texts for prompt in prompts)
+
+
+def test_measurement_calibration_corpus_builds_with_frozen_split() -> None:
+    backend = FakeCalibrationBackend()
+    artifact = build_real_measurement_calibration_corpus(backend, seed_base=6000)
+    assert len(artifact.manifest.samples) == MEASUREMENT_CALIBRATION_SAMPLE_COUNT == 1280
+    assert artifact.negative_count == MEASUREMENT_CALIBRATION_NEGATIVE_COUNT == 1024
+    assert artifact.audit_count == MEASUREMENT_CALIBRATION_AUDIT_COUNT == 256
+    calibration = artifact.calibration_samples()
+    audit = artifact.audit_samples()
+    assert len(calibration) == 1024
+    assert len(audit) == 256
+    assert not {sample.sample_id for sample in calibration} & {sample.sample_id for sample in audit}
+    assert all(sample.split is CorpusSplit.THRESHOLD_CALIBRATION for sample in artifact.manifest.samples)
+    assert all(sample.label is WatermarkLabel.UNWATERMARKED for sample in artifact.manifest.samples)
+    text = canonical_json_text(artifact) + "\n"
+    assert len(text) > 0
+
+
+def test_measurement_calibration_rejects_wrong_sample_count() -> None:
+    backend = FakeCalibrationBackend()
+    prompts = build_measurement_calibration_prompt_records()
+    with pytest.raises(Exception):
+        build_measurement_calibration_corpus("bad-corpus", prompts, ())
diff --git a/tests/test_measurement_threshold.py b/tests/test_measurement_threshold.py
new file mode 100644
index 00000000..c7a1297c
--- /dev/null
+++ b/tests/test_measurement_threshold.py
@@ -0,0 +1,81 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+
+import fuckmark.experiments.measurement_threshold as mt
+from fuckmark.experiments.measurement_threshold import (
+    build_fixed_threshold_artifact,
+    validate_fixed_threshold_artifact,
+)
+
+
+class _FakeCalibrationCorpus:
+    def __init__(self, calibration_scores, audit_scores) -> None:
+        self.calibration_set = tuple(
+            SimpleNamespace(sample_id=f"cal-{index}", score=value)
+            for index, value in enumerate(calibration_scores)
+        )
+        self.audit_set = tuple(
+            SimpleNamespace(sample_id=f"audit-{index}", score=value)
+            for index, value in enumerate(audit_scores)
+        )
+        self.artifact_hash = "a" * 64
+        self.manifest = SimpleNamespace(corpus_id="fake-calibration")
+
+    def calibration_samples(self):
+        return self.calibration_set
+
+    def audit_samples(self):
+        return self.audit_set
+
+
+def _patch_scoring(monkeypatch, calibration_scores, audit_scores):
+    corpus = _FakeCalibrationCorpus(calibration_scores, audit_scores)
+    lookup = {sample.sample_id: sample.score for sample in (*corpus.calibration_set, *corpus.audit_set)}
+
+    def fake_evidence(sample, adapter):
+        return SimpleNamespace(raw_score=lookup[sample.sample_id])
+
+    def fake_calibrate(evidence, scope, target_fprs, comparison_operator, confidence_level):
+        return SimpleNamespace(
+            detector_identity=SimpleNamespace(identity_hash="d" * 64),
+            bundle_hash="b" * 64,
+        )
+
+    monkeypatch.setattr(mt, "_text_only_weighted_evidence", fake_evidence)
+    monkeypatch.setattr(mt, "calibrate_detector", fake_calibrate)
+    return corpus
+
+
+def test_fixed_threshold_uses_frozen_order_statistic(monkeypatch) -> None:
+    calibration = [index / 2000.0 for index in range(1024)]
+    audit = [0.0] * 250 + [0.9] * 6
+    corpus = _patch_scoring(monkeypatch, calibration, audit)
+    artifact = build_fixed_threshold_artifact(corpus, None, frozen_at_utc="2026-08-23T00:00:00+00:00")
+    ordered = sorted(calibration)
+    assert artifact["threshold_order_statistic"] == 1015
+    assert artifact["threshold"] == ordered[1014]
+    assert artifact["calibration_exceedances"] == 10
+    assert artifact["audit_exceedances"] == 6
+    assert artifact["audit_realized_fpr"] == 6 / 256
+    assert artifact["detector_identity_hash"] == "d" * 64
+    assert artifact["artifact_hash"]
+
+
+def test_fixed_threshold_validation_rejects_mismatches(monkeypatch) -> None:
+    calibration = [index / 2000.0 for index in range(1024)]
+    corpus = _patch_scoring(monkeypatch, calibration, [0.0] * 256)
+    artifact = build_fixed_threshold_artifact(corpus, None, frozen_at_utc="2026-08-23T00:00:00+00:00")
+    assert validate_fixed_threshold_artifact(artifact, "d" * 64) == artifact["threshold"]
+    with pytest.raises(ValueError):
+        validate_fixed_threshold_artifact(artifact, "e" * 64)
+    tampered = dict(artifact)
+    tampered["threshold"] = 0.123456
+    with pytest.raises(ValueError):
+        validate_fixed_threshold_artifact(tampered, "d" * 64)
+    bad_version = dict(artifact)
+    bad_version["algorithm_version"] = "other-v1"
+    with pytest.raises(ValueError):
+        validate_fixed_threshold_artifact(bad_version, "d" * 64)
diff --git a/tests/test_protected_currency_context_invariance.py b/tests/test_protected_currency_context_invariance.py
new file mode 100644
index 00000000..8cafde79
--- /dev/null
+++ b/tests/test_protected_currency_context_invariance.py
@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+import pytest
+
+from fuckmark.transforms import validate_hard_invariants
+from fuckmark.transforms.protected import ProtectedSpanExtractor
+
+
+def _currency_spans(text: str) -> list[str]:
+    return [
+        text[span.start : span.end]
+        for span in ProtectedSpanExtractor().extract(text).spans
+        if "currency" in tuple(kind.value for kind in span.kinds)
+    ]
+
+
+def test_currency_extraction_is_invariant_under_preceding_whitespace() -> None:
+    assert _currency_spans("for $100") == ["$100"]
+    assert _currency_spans("for  $100") == ["$100"]
+    assert _currency_spans("a  $5 and $100") == ["$5", "$100"]
+    assert _currency_spans("cost:  $100,000 total") == ["$100,000"]
+
+
+def test_signed_currency_forms_still_extract() -> None:
+    assert _currency_spans("- $5") == ["- $5"]
+    assert _currency_spans("+EUR  3.50") == ["+EUR  3.50"]
+    assert _currency_spans("USD  5") == ["USD  5"]
+
+
+def test_spacing_before_currency_no_longer_breaks_hard_invariants() -> None:
+    source = "Apple has been selling its iPhones for $100, and buyers notice."
+    transformed = "Apple has been  selling its iPhones for  $100,  and buyers notice."
+    report = validate_hard_invariants(source, transformed)
+    assert report.status.value == "pass"
+    assert [r.value for r in report.reasons] == []
diff --git a/tests/test_tiny_dev_corpus_v3.py b/tests/test_tiny_dev_corpus_v3.py
new file mode 100644
index 00000000..343f57be
--- /dev/null
+++ b/tests/test_tiny_dev_corpus_v3.py
@@ -0,0 +1,179 @@
+from __future__ import annotations
+
+from collections import defaultdict
+
+import pytest
+
+from fuckmark.config import canonical_json_text
+from fuckmark.corpus import (
+    CorpusDomain,
+    CorpusSplit,
+    GenerationParameters,
+    KeySplit,
+    ModelTokenizerIdentity,
+    PaddingSide,
+    WatermarkCondition,
+    WatermarkLabel,
+    TINY_DEV_V3_CORPUS_ALGORITHM_VERSION,
+    TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN,
+    build_tiny_dev_v3_prompt_records,
+    build_real_tiny_dev_v3_corpus,
+    parse_tiny_dev_v3_corpus_json,
+)
+from fuckmark.corpus.tiny_dev_generation import (
+    TINY_DEV_SEED_POLICY_ID,
+    TinyDevGeneratedContinuation,
+    build_tiny_dev_prompt_records,
+)
+from fuckmark.corpus.tiny_dev_io_v3 import load_tiny_dev_corpus_by_version_json
+from fuckmark.hashing import sha256_json, sha256_text
+
+
+class FakeTinyDevV3Backend:
+    def __init__(self) -> None:
+        self._model = ModelTokenizerIdentity.create(
+            model_id="example/tiny-dev-model",
+            model_revision="a" * 40,
+            tokenizer_id="example/tiny-dev-tokenizer",
+            tokenizer_revision="b" * 40,
+            chat_template_present=False,
+            chat_template_hash=sha256_text(""),
+            special_token_map_hash=sha256_json({"eos_token": "<eos>", "pad_token": "<pad>"}),
+            padding_side=PaddingSide.LEFT,
+            bos_token_id=None,
+            eos_token_id=2,
+            pad_token_id=0,
+            add_bos_token=False,
+            add_eos_token=False,
+        )
+        self._watermark = WatermarkCondition.create(
+            sha256_json({"ngram_len": 5, "keys": (1, 2, 3)}),
+            KeySplit.DEV,
+            "dev-test-key",
+        )
+
+    @property
+    def model_identity(self) -> ModelTokenizerIdentity:
+        return self._model
+
+    @property
+    def watermark_condition(self) -> WatermarkCondition:
+        return self._watermark
+
+    def generation_parameters(self, seed: int) -> GenerationParameters:
+        return GenerationParameters.create(
+            seed=seed,
+            seed_policy_id=TINY_DEV_SEED_POLICY_ID,
+            temperature=0.8,
+            top_k=50,
+            top_p=0.95,
+            max_new_tokens=64,
+            do_sample=True,
+            dtype="float32",
+            device="cpu",
+            backend_id="fake-tiny-dev",
+            backend_version="1",
+        )
+
+    def generate(self, prompt: str, seed: int, *, watermarked: bool) -> TinyDevGeneratedContinuation:
+        prompt_token = 10 + (sum(prompt.encode("utf-8")) % 1000)
+        label_offset = 100_000 if watermarked else 200_000
+        continuation = tuple(
+            label_offset + ((seed * 131 + index) % 90_000)
+            for index in range(64)
+        )
+        text = (
+            f"{'watermarked' if watermarked else 'control'} output for "
+            f"{sha256_text(prompt)[:12]} seed {seed}"
+        )
+        text_only = tuple(300_000 + ((seed * 17 + index) % 80_000) for index in range(16))
+        return TinyDevGeneratedContinuation(
+            text=text,
+            input_token_ids=(prompt_token, prompt_token + 1),
+            attention_mask=(1, 1),
+            continuation_token_ids=continuation,
+            text_only_token_ids=text_only,
+        )
+
+
+def test_v3_prompt_records_preserve_v2_calibration_and_extend_attack() -> None:
+    v2 = build_tiny_dev_prompt_records()
+    v3 = build_tiny_dev_v3_prompt_records(16)
+    v2_calibration = {prompt.text for prompt in v2 if prompt.split is CorpusSplit.THRESHOLD_CALIBRATION}
+    v3_calibration = {prompt.text for prompt in v3 if prompt.split is CorpusSplit.THRESHOLD_CALIBRATION}
+    assert v2_calibration == v3_calibration
+    v2_attack = {prompt.text for prompt in v2 if prompt.split is CorpusSplit.ATTACK_DEVELOPMENT}
+    v3_one = build_tiny_dev_v3_prompt_records(1)
+    v3_one_attack = {prompt.text for prompt in v3_one if prompt.split is CorpusSplit.ATTACK_DEVELOPMENT}
+    assert v2_attack == v3_one_attack
+    counts: defaultdict[tuple[CorpusSplit, CorpusDomain], int] = defaultdict(int)
+    for prompt in v3:
+        counts[(prompt.split, prompt.domain)] += 1
+    for domain in CorpusDomain:
+        assert counts[(CorpusSplit.THRESHOLD_CALIBRATION, domain)] == 25
+        assert counts[(CorpusSplit.ATTACK_DEVELOPMENT, domain)] == 16
+    assert len({prompt.prompt_id for prompt in v3}) == 164
+    assert len({prompt.prompt_family_id for prompt in v3}) == 164
+
+
+@pytest.mark.parametrize("count", (0, -1, TINY_DEV_V3_MAX_ATTACK_PAIRS_PER_DOMAIN + 1))
+def test_v3_prompt_records_reject_out_of_range_attack_pairs(count: int) -> None:
+    with pytest.raises((ValueError, Exception)):
+        build_tiny_dev_v3_prompt_records(count)
+
+
+def test_real_v3_runner_builds_parameterized_paired_corpus() -> None:
+    backend = FakeTinyDevV3Backend()
+    artifact = build_real_tiny_dev_v3_corpus(
+        backend,
+        seed_base=5000,
+        attack_pairs_per_domain=8,
+    )
+    assert artifact.algorithm_version == TINY_DEV_V3_CORPUS_ALGORITHM_VERSION
+    assert artifact.attack_pairs_per_domain == 8
+    assert artifact.calibration_pairs_per_domain == 25
+    assert len(artifact.manifest.prompts) == 132
+    assert len(artifact.manifest.samples) == 264
+    attack_watermarked = [
+        sample
+        for sample in artifact.manifest.samples
+        if sample.split is CorpusSplit.ATTACK_DEVELOPMENT
+        and sample.label is WatermarkLabel.WATERMARKED
+    ]
+    assert len(attack_watermarked) == 32
+    assert all(sample.watermark.key_split is KeySplit.DEV for sample in artifact.manifest.samples)
+    assert len({sample.text_sha256 for sample in artifact.manifest.samples}) == 264
+
+
+def test_v3_corpus_json_replays_canonically_and_version_dispatch_loads() -> None:
+    backend = FakeTinyDevV3Backend()
+    artifact = build_real_tiny_dev_v3_corpus(
+        backend,
+        seed_base=9000,
+        attack_pairs_per_domain=2,
+    )
+    text = canonical_json_text(artifact) + "\n"
+    replay = parse_tiny_dev_v3_corpus_json(text)
+    assert replay == artifact
+    assert replay.artifact_hash == artifact.artifact_hash
+
+
+def test_v3_builder_rejects_mismatched_prompt_profile() -> None:
+    from fuckmark.corpus import build_tiny_dev_v3_corpus
+
+    backend = FakeTinyDevV3Backend()
+    prompts = build_tiny_dev_v3_prompt_records(4)
+    with pytest.raises(Exception):
+        build_tiny_dev_v3_corpus(
+            "mismatch-corpus",
+            prompts,
+            (),
+            attack_pairs_per_domain=8,
+        )
+
+
+def test_version_dispatch_loader_rejects_unknown_version(tmp_path) -> None:
+    bad = tmp_path / "corpus.json"
+    bad.write_text('{"algorithm_version": "tiny-dev-corpus-v9"}', encoding="utf-8")
+    with pytest.raises(Exception):
+        load_tiny_dev_corpus_by_version_json(bad)
diff --git a/tools/budget_scaled_coverage_diagnosis.py b/tools/budget_scaled_coverage_diagnosis.py
new file mode 100644
index 00000000..e73dd5f2
--- /dev/null
+++ b/tools/budget_scaled_coverage_diagnosis.py
@@ -0,0 +1,157 @@
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+from fuckmark.corpus import load_tiny_dev_corpus_by_version_json
+from fuckmark.experiments.effectiveness_plan import _attack_samples, _encode_with_offsets
+from fuckmark.hashing import sha256_json
+from fuckmark.transforms import (
+    SchedulePolicy,
+    CandidateScheduler,
+    KeyBlindScheduleInput,
+    ScheduleGeometryMode,
+    build_candidate_tokenizer_geometry,
+    key_blind_high_coverage_transform_registry,
+)
+from fuckmark.coverage import union_size, merge_intervals
+
+
+DIAGNOSIS_VERSION = "budget-scaled-coverage-diagnosis-v1"
+
+
+def diagnose_sources(corpus, tokenizer, plan, evidence) -> dict[str, object]:
+    registry = key_blind_high_coverage_transform_registry()
+    scheduler = CandidateScheduler()
+    evidence_rows = {
+        row["variant_hash"]: row for row in evidence["rows"]
+    }
+    rows = []
+    for variant in plan["variants"]:
+        if variant["requested_budget"] != plan["budgets"][0]:
+            continue
+        row_evidence = evidence_rows[variant["variant_hash"]]
+        source = next(
+            sample
+            for sample in corpus.manifest.samples
+            if sample.sample_id == variant["source_sample_id"]
+        )
+        token_ids, offsets = _encode_with_offsets(tokenizer, source)
+        enumeration = registry.enumerate(source.text)
+        geometry = build_candidate_tokenizer_geometry(
+            source.text,
+            enumeration,
+            token_ids,
+            offsets,
+            tokenizer_identity_hash=source.model.identity_hash,
+            ngram_len=5,
+        )
+        coverage = geometry.coverage_mapping()
+        observation_count = max(0, len(token_ids) - 5 + 1)
+        achievable = union_size(
+            interval
+            for intervals in coverage.values()
+            for interval in intervals
+        ) if coverage else 0
+        selected_ids = set(variant["selected_candidate_ids"])
+        realized = union_size(
+            interval
+            for candidate_id, intervals in coverage.items()
+            if candidate_id in selected_ids
+            for interval in intervals
+        ) if coverage else 0
+        hole_intervals = []
+        covered = merge_intervals(
+            interval
+            for intervals in coverage.values()
+            for interval in intervals
+        ) if coverage else ()
+        cursor = 0
+        for interval in covered:
+            start, end = interval.start, interval.end_exclusive
+            if start > cursor:
+                hole_intervals.append((cursor, start))
+            cursor = max(cursor, end)
+        if cursor < observation_count:
+            hole_intervals.append((cursor, observation_count))
+        rows.append(
+            {
+                "source_sample_id": variant["source_sample_id"],
+                "source_label": variant["source_label"],
+                "domain": variant["domain"],
+                "observation_count": observation_count,
+                "candidate_count": variant["candidate_count"],
+                "realized_edit_cost": variant["realized_edit_cost"],
+                "achievable_coverage_fraction": achievable / observation_count if observation_count else 0.0,
+                "realized_coverage_fraction": realized / observation_count if observation_count else 0.0,
+                "hole_count": len(hole_intervals),
+                "hole_token_total": sum(end - start for start, end in hole_intervals),
+                "pristine_score": row_evidence["pristine_score"],
+                "transformed_score": row_evidence["transformed_score"],
+                "transformed_detected": row_evidence["transformed_detected"],
+                "score_drop": row_evidence["score_drop"],
+            }
+        )
+    watermarked = [row for row in rows if row["source_label"] == "watermarked"]
+    detected = [row for row in watermarked if row["transformed_detected"]]
+    escaped = [row for row in watermarked if not row["transformed_detected"]]
+
+    def _mean(values):
+        return sum(values) / len(values) if values else None
+
+    payload = {
+        "algorithm_version": DIAGNOSIS_VERSION,
+        "analysis_scope": "post-hoc explanatory analysis of the completed budget-scaled confirmation cycle; not used to tune any candidate against this corpus",
+        "plan_hash": plan["plan_hash"],
+        "evidence_hash": evidence["artifact_hash"],
+        "corpus_hash": corpus.artifact_hash,
+        "rows": tuple(rows),
+        "watermarked_summary": {
+            "total": len(watermarked),
+            "detected": len(detected),
+            "mean_achievable_coverage_detected": _mean([r["achievable_coverage_fraction"] for r in detected]),
+            "mean_achievable_coverage_escaped": _mean([r["achievable_coverage_fraction"] for r in escaped]),
+            "mean_realized_coverage_detected": _mean([r["realized_coverage_fraction"] for r in detected]),
+            "mean_realized_coverage_escaped": _mean([r["realized_coverage_fraction"] for r in escaped]),
+            "mean_hole_token_total_detected": _mean([r["hole_token_total"] for r in detected]),
+            "mean_hole_token_total_escaped": _mean([r["hole_token_total"] for r in escaped]),
+            "achievable_below_70pct_detected": sum(1 for r in detected if r["achievable_coverage_fraction"] < 0.7),
+            "achievable_below_70pct_escaped": sum(1 for r in escaped if r["achievable_coverage_fraction"] < 0.7),
+        },
+    }
+    return {**payload, "artifact_hash": sha256_json(payload)}
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(prog="budget-scaled-coverage-diagnosis")
+    parser.add_argument("--corpus-json", type=Path, required=True)
+    parser.add_argument("--plan-json", type=Path, required=True)
+    parser.add_argument("--evidence-json", type=Path, required=True)
+    parser.add_argument("--json", type=Path, required=True)
+    args = parser.parse_args(argv)
+    from transformers import AutoTokenizer
+
+    corpus = load_tiny_dev_corpus_by_version_json(args.corpus_json)
+    plan = json.loads(args.plan_json.read_text(encoding="utf-8"))
+    evidence = json.loads(args.evidence_json.read_text(encoding="utf-8"))
+    tokenizer = AutoTokenizer.from_pretrained(
+        "openai-community/gpt2",
+        revision="607a30d783dfa663caf39e06633721c8d4cfcd7e",
+        use_fast=True,
+        padding_side="left",
+    )
+    report = diagnose_sources(corpus, tokenizer, plan, evidence)
+    args.json.parent.mkdir(parents=True, exist_ok=True)
+    args.json.write_text(
+        json.dumps(report, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+    )
+    summary = report["watermarked_summary"]
+    print(f"artifact_hash={report['artifact_hash']}")
+    for key, value in summary.items():
+        print(f"{key}={value}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tools/budget_scaled_render_page.py b/tools/budget_scaled_render_page.py
new file mode 100644
index 00000000..9e0fbd7b
--- /dev/null
+++ b/tools/budget_scaled_render_page.py
@@ -0,0 +1,88 @@
+from __future__ import annotations
+
+import argparse
+import html
+import json
+from pathlib import Path
+
+
+def _load(path: Path) -> dict:
+    value = json.loads(path.read_text(encoding="utf-8"))
+    if not isinstance(value, dict):
+        raise ValueError("expected a JSON object")
+    return value
+
+
+def _load_corpus_texts(corpus_path: Path) -> dict[str, str]:
+    corpus = _load(corpus_path)
+    return {sample["sample_id"]: sample["text"] for sample in corpus["manifest"]["samples"]}
+
+
+def build_render_page(plan: dict, corpus_texts: dict[str, str]) -> tuple[str, list[dict]]:
+    blocks: list[str] = []
+    manifest: list[dict] = []
+    for index, variant in enumerate(plan["variants"]):
+        source_id = variant["source_sample_id"]
+        source_text = corpus_texts[source_id]
+        transformed_text = variant["transformed_text"]
+        blocks.append(
+            "<section class=\"pair\" id=\"pair-{index}\">"
+            "<h2>Pair {index}: {source_id} (budget {budget})</h2>"
+            "<div class=\"source\" data-pair=\"{index}\" data-role=\"source\">{source}</div>"
+            "<div class=\"transformed\" data-pair=\"{index}\" data-role=\"transformed\">{transformed}</div>"
+            "</section>".format(
+                index=index,
+                source_id=html.escape(source_id),
+                budget=variant["requested_budget"],
+                source=html.escape(source_text),
+                transformed=html.escape(transformed_text),
+            )
+        )
+        manifest.append(
+            {
+                "pair_index": index,
+                "source_sample_id": source_id,
+                "requested_budget": variant["requested_budget"],
+                "source_text_hash": variant["source_text_hash"],
+                "transformed_text_hash": variant["transformed_text_hash"],
+                "variant_hash": variant["variant_hash"],
+            }
+        )
+    page = (
+        "<!DOCTYPE html><html><head><meta charset=\"utf-8\">"
+        "<title>FuckMark budget-scaled render check</title>"
+        "<style>body{font-family:monospace;margin:20px;} "
+        ".pair{border:1px solid #999;margin:16px 0;padding:8px;} "
+        ".source{background:#f4f4f4;white-space:pre-wrap;} "
+        ".transformed{background:#e8f4e8;white-space:pre-wrap;} "
+        "h2{font-size:14px;}</style></head><body>"
+        + "".join(blocks)
+        + "</body></html>"
+    )
+    return page, manifest
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(prog="budget-scaled-render-page")
+    parser.add_argument("--corpus-json", type=Path, required=True)
+    parser.add_argument("--plan-json", type=Path, required=True)
+    parser.add_argument("--html", type=Path, required=True)
+    parser.add_argument("--manifest-json", type=Path, required=True)
+    args = parser.parse_args(argv)
+    plan = _load(args.plan_json)
+    corpus_texts = _load_corpus_texts(args.corpus_json)
+    page, manifest = build_render_page(plan, corpus_texts)
+    args.html.parent.mkdir(parents=True, exist_ok=True)
+    args.html.write_text(page, encoding="utf-8")
+    args.manifest_json.write_text(
+        json.dumps({"pair_count": len(manifest), "plan_hash": plan["plan_hash"], "pairs": manifest}, indent=2, sort_keys=True) + "\n",
+        encoding="utf-8",
+    )
+    print(f"pair_count={len(manifest)}")
+    print(f"html={args.html.as_posix()}")
+    print(f"manifest_json={args.manifest_json.as_posix()}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())