rosetta[yaml]: cross-language consistency — 9 red / 8 amber metrics, 2 ledgered shapes

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Part of #2560 — per-language tracking for the keyword-rosetta control corpus (built for #1096). Planted intent is identical in every language, so every deviation below is measured bias vs. the 46-language median, validated in the corpus's deviation ledger. 🔴 = beyond ±50% of the cross-language median, 🟡 = ±25–50%.

Triage order (per the epic): structure detection first, then signal/keyword rules, then risk-score consequences — §3's numbers are downstream of §1–§2 and re-baseline as those fix. Cross-cutting engine issues (e.g. #2535/#2546) fix many languages at once; this issue tracks this language's residual after each cross-cutting fix lands, and closes when the language sits inside the ±25% band on every comparable metric (or every remaining deviation is ledgered as intended morphology).

1. Structure detection (fix first)

• 🔴 args: 0 vs median 13 (-100%)
• 🔴 dependency_links: 0 vs median 3 (-100%)
• 🔴 functions_found: 3 vs median 13 (-77%)

2. Signal / keyword deviations

• 🔴 cleanup: 0 vs median 2 (-100%)
• 🔴 doc: 2 vs median 1 (+100%)
• 🔴 ownership: 0 vs median 1 (-100%)
• 🔴 state_mutation: 1 vs median 6 (-83%)
• 🟡 branch: 3 vs median 5 (-40%)
• 🟡 comment_lines: 15 vs median 30 (-50%)
• 🟡 keyword_hits: 176 vs median 247.5 (-29%)
• 🟡 safety: 1 vs median 2 (-50%)
• 🟡 safety_bypasses: 1 vs median 2 (-50%)
• 🟡 test: 1 vs median 2 (-50%)

3. Risk-exposure consequences (downstream)

• 🔴 risk_api_exposure: 0 vs median 5.31104 (-100%)
• 🔴 risk_cognitive_load: 5.68942 vs median 15.1444 (-62%)
• 🟡 risk_documentation: 42.7904 vs median 57.1208 (-25%)
• 🟡 risk_tech_debt: 20 vs median 39.9576 (-50%)

Ledgered shapes touching yaml

defect	type	issue	evidence	summary
census-requires-git-tracked	engine-semantic	—	—	GalaxyScope's census enumerates git-tracked files only; an untracked folder scans as '0 files mapped' with no per-file warning
batch5-tier2-morphology-shapes	keyword-overlap	—	—	Collective entry for Tier-2 finditer/report-confirmed shapes, detailed per-manifest: css at-rules triple-count (func+branch, @supports also safety; args tracks @import u…

Reproduce / evidence

• Corpus folder: data/yaml/ — expected_signals.json carries the shape-by-shape accounting
• Gate: GALAXYSCOPE_BIN=<venv>/bin/galaxyscope python tools/verify_language.py yaml in the corpus repo
• Full context: findings_by_language.md#yaml · bias_report.md · bias chart