Voice Agent TestOps

Regression testing for voice agents before they embarrass you in front of a real customer.

Voice Agent TestOps runs scripted customer conversations against your agent, then checks the things demos usually hide: unsafe pricing, over-promising, missed phone numbers, wrong handoff intent, and latency that quietly kills the experience.

It is not another voice-agent framework. It is the safety harness you put around agents built with OpenClaw, Vapi, Retell, LiveKit, Pipecat, Twilio, SIP trunks, or your own HTTP service.

Quick Start · Example Library · Create Mock Data · Connect An Agent · Turn A Real Failure Into A Regression Test · Draft Regressions From Failed Reports · Import Production Calls For Sampling · Suite Format

Why This Exists

Voice agents fail in strangely expensive ways.

They quote a price that was never approved. They promise a slot that is already booked. They sound helpful but forget to collect the phone number. They say they will transfer to a human, then classify the lead as other. A normal unit test will not catch that. A happy-path demo will not reveal it either.

Voice Agent TestOps gives you a small, repeatable gate:

Write the risky customer scenario once.
Run it against every agent build.
Get a report a human can read and a JSON artifact CI can enforce.

If you are building voice agents for real businesses, this repo is meant to be the boring little alarm bell that rings before production does.

What It Catches

Risk	Example failure	Assertion
Unsafe pricing	"The cheapest package is guaranteed."	`must_not_match`
Missing facts	Agent never says the configured `599-1299` package range	`must_contain_any`
Lead leakage	Customer gives a phone number, summary has no `phone`	`lead_field_present`
Wrong intent	Handoff request classified as `pricing`	`lead_intent`
Slow turns	One response takes 12 seconds	`max_latency_ms`

Quick Start

Create a starter suite. No API key required.

npx voice-agent-testops init
npx voice-agent-testops validate --suite voice-testops/suite.json
npx voice-agent-testops run --suite voice-testops/suite.json

Expected output:

Example Photo Studio Voice Agent TestOps: passed (0 failures, 4 assertions)
JSON report: .voice-testops/report.json
HTML report: .voice-testops/report.html

Connecting a real HTTP agent?

npx voice-agent-testops init --stack http --name "Lumen Portrait Studio" --with-ci
npx voice-agent-testops doctor --agent http --endpoint http://localhost:3000/test-turn --suite voice-testops/suite.json

Want a different vertical or language?

npx voice-agent-testops list --lang en
npx voice-agent-testops init --industry restaurant --lang en --name "Maple Bistro"

Generate a more polished merchant-facing report:

npx voice-agent-testops run --suite examples/voice-testops/photo-studio-multiturn-suite.json
npm run report:export

Artifacts:

.voice-testops/report.json for CI and automation
.voice-testops/report.html for debugging and walkthroughs
.voice-testops/summary.md for GitHub Actions step summaries
.voice-testops/junit.xml for CI test dashboards
.voice-testops/diff.md for comparing this run with a baseline report
.voice-testops/report.pdf for customers or internal review
.voice-testops/report.png for quick sharing

Example Library

Most public examples are bilingual. Mature business verticals keep Chinese and English suites with the same risk shape, while newer recording-derived suites may start with a reviewed Chinese sample.

Vertical	Chinese suite	English suite	Risks covered
Dental clinic	chinese-dental-clinic-suite.json	english-dental-clinic-suite.json	Treatment guarantees, dentist availability, phone capture
Restaurant booking	chinese-restaurant-booking-suite.json	english-restaurant-booking-suite.json	Unconfirmed tables, minimum-spend claims, booking details
Real estate agent	chinese-real-estate-agent-suite.json	english-real-estate-agent-suite.json	Investment promises, listing status, viewing lead capture
Insurance regulated service	chinese-insurance-regulated-service-suite.json	english-insurance-regulated-service-suite.json	Identity verification, claim status, coverage eligibility, licensed-agent handoff
Outbound lead generation	chinese-outbound-leadgen-suite.json, chinese-outbound-recording-seeds-suite.json	Not yet available	Refusal handling, private-channel consent, gift promises, age and child-data confirmation

Explore the full catalog from your terminal:

npx voice-agent-testops list
npx voice-agent-testops list --lang en
npx voice-agent-testops list --industry restaurant
npx voice-agent-testops list --industry outbound_leadgen

Create Mock Data

The examples are generated from a simple contract: merchant facts, risky customer questions, and assertions that encode what the agent must say, must not say, and must capture. You can start with a generated mock suite, then replace the sample facts with a real merchant profile.

npx voice-agent-testops init --industry restaurant --lang en --name "Maple Bistro"
npx voice-agent-testops validate --suite voice-testops/suite.json
npx voice-agent-testops run --suite voice-testops/suite.json

Supported starter verticals are photography, dental_clinic, restaurant, real_estate, home_design, and insurance. Supported languages are en and zh-CN.

For the recipe behind the examples, see the Mock data guide. It shows how to turn a merchant fact sheet into reviewable suites without guessing, overfitting, or needing an LLM.

Editor Autocomplete

Export the suite JSON Schema when you want VS Code to autocomplete scenario fields, assertion types, lead intents, sources, industries, and severity values:

npx voice-agent-testops schema --out voice-testops/voice-test-suite.schema.json

Add this to .vscode/settings.json:

{
  "json.schemas": [
    {
      "fileMatch": ["voice-testops/suite.json", "**/*suite.json"],
      "url": "./voice-testops/voice-test-suite.schema.json"
    }
  ]
}

The schema describes the raw authoring format, so both inline merchant objects and merchantRef files get editor hints.

Connect An Agent

Start with HTTP if you want the shortest path. Use the OpenClaw adapter when you already have an OpenClaw-compatible /v1/responses endpoint. For hosted voice stacks, add a small test bridge so CI can test the same prompt, tool, and lead-summary logic without placing a real phone call. If the only real entry point is a SIP number or trunk, use the SIP driver contract to place a voice call while keeping the same suite and report format.

Generic HTTP Agent

Want a running example first?

Terminal 1:

npm run example:http-agent

Terminal 2:

npm run voice-test -- \
  --suite examples/voice-testops/openclaw-suite.json \
  --agent http \
  --endpoint http://127.0.0.1:4318/test-turn

The example lives at examples/http-agent-server/server.mjs. Replace its createTestAgentResponse() function with your real agent call when you are ready.

Building on Vapi or Retell? Start the platform bridge example instead:

npm run example:voice-platform-bridge

It exposes http://127.0.0.1:4319/test-turn for deterministic CI runs, plus /vapi/webhook and /retell/webhook for platform webhook smoke tests. See Vapi and Retell for the 30-minute runbooks.

Before running a full suite, ask doctor whether your bridge speaks the right contract:

npx voice-agent-testops doctor \
  --agent http \
  --endpoint http://127.0.0.1:4318/test-turn \
  --suite voice-testops/suite.json

Healthy output:

Voice Agent TestOps doctor
Suite valid: ok
Probe scenario: pricing_safety
Endpoint reachable: ok
spoken: ok
summary: ok
Doctor passed

Your endpoint receives one test turn:

npm run voice-test -- \
  --suite examples/voice-testops/openclaw-suite.json \
  --agent http \
  --endpoint "https://your-agent.example.com/test-turn"

Request shape:

{
  "suiteName": "回归测试",
  "scenarioId": "pricing",
  "turnIndex": 0,
  "customerText": "单人写真多少钱",
  "source": "website",
  "merchant": {},
  "messages": []
}

Response shape:

{
  "spoken": "单人写真一般是 599-1299 元，档期需要人工确认。",
  "summary": {
    "source": "website",
    "intent": "pricing",
    "level": "medium",
    "need": "客户咨询单人写真价格",
    "questions": ["单人写真多少钱"],
    "nextAction": "人工确认档期后跟进",
    "transcript": []
  },
  "audio": {
    "url": "https://your-agent.example.com/replays/call-123-turn-1.wav",
    "durationMs": 4200
  },
  "voiceMetrics": {
    "timeToFirstWordMs": 640,
    "silenceMs": 850,
    "asrConfidence": 0.93
  }
}

spoken is required. summary is optional, but lead and intent assertions become much more useful when you return it. audio and voiceMetrics are also optional; return them when you want replay links in the report or voice-native assertions such as audio_replay_present, voice_metric_max, and voice_metric_min.

OpenClaw-compatible Endpoint

npm run voice-test -- \
  --suite examples/voice-testops/openclaw-suite.json \
  --agent openclaw \
  --endpoint "$OPENCLAW_AGENT_URL" \
  --api-key "$OPENCLAW_API_KEY" \
  --openclaw-mode responses

For a local OpenClaw Gateway setup, see docs/ops/openclaw-docker.md.

SIP Voice Agents

When your bot only accepts real SIP calls, run with --agent sip and point Voice Agent TestOps at a driver command. The driver receives each test turn as JSON on stdin, places or controls the SIP call, plays customerText, records and transcribes the bot reply, then returns { "spoken": string, "audio"?: object, "voiceMetrics"?: object }.

npm run voice-test -- \
  --suite examples/voice-testops/chinese-real-estate-agent-suite.json \
  --agent sip \
  --sip-uri sip:+8613800000000@10.0.0.8 \
  --sip-driver-command "node examples/sip-driver/mock-driver.mjs" \
  --sip-media-dir .voice-testops/sip-media \
  --sip-driver-retries 2

The bundled mock driver does not dial; it verifies the adapter contract. For a real local SIP smoke test, use node examples/sip-driver/baresip-driver.mjs with private SIP credentials in environment variables. Use --sip-driver-retries for one or two redials when the trunk occasionally misses call setup. Replace either driver with your SIPp, Asterisk, baresip, LiveKit SIP, Twilio, or internal dialer script for production E2E voice tests. See SIP Voice Agents.

Integration Guides

Sales Demo

If you already have a local OpenClaw Gateway running with a model provider configured:

npm run sales:demo

This runs the photo-studio multi-turn suite and exports a customer-ready report. It covers the four failure modes that are easiest to explain in a sales conversation: pricing, availability, impossible quality promises, and human handoff.

Turn A Real Failure Into A Regression Test

When a pilot replies with one sanitized transcript, start with the intake wrapper. It writes a private suite draft, merchant draft, and triage summary without quoting the raw transcript in the summary:

pbpaste | npx voice-agent-testops transcript-trial \
  --stdin \
  --out-dir .voice-testops/transcript-trial \
  --merchant-name "Pilot demo agent" \
  --industry outbound_leadgen \
  --customer "Pilot demo agent"

transcript-trial is the lowest-friction path when there is no endpoint yet. It uses the sanitized transcript as a replay source, generates a suite, merchant draft, intake summary, JSON/HTML/Markdown/JUnit reports, commercial-report.md, pilot-recap.md, and proof-card.md. If the replayed transcript fails the generated assertions, it also writes regression-draft.json and failure-clusters.md.

If you already have a reviewed suite and only need to replay a saved transcript, use the transcript agent directly:

npx voice-agent-testops run \
  --suite voice-testops/suite.json \
  --agent transcript \
  --transcript .voice-testops/transcripts/sanitized-call.txt

For triage only, without running a replay report, use transcript-intake:

pbpaste | npx voice-agent-testops transcript-intake \
  --stdin \
  --suite .voice-testops/transcript-intake/suite.json \
  --merchant-out .voice-testops/transcript-intake/merchant.json \
  --summary .voice-testops/transcript-intake/summary.md \
  --merchant-name "Pilot demo agent"

Use this before a live endpoint is ready. The summary highlights inferred industry, turn counts, assertion mix, risk signals, privacy warnings, generated artifacts, and the next validate / doctor / run commands. It does not print raw transcript text.

Paste a failed call and generate a starter suite plus an editable merchant draft:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --preview \
  --merchant-name "Lumen Portrait Studio"

When the preview looks right, write the files:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --out voice-testops/suite.json \
  --merchant-out voice-testops/merchant.json \
  --merchant-name "Lumen Portrait Studio" \
  --name "Generated transcript regression" \
  --source website

For insurance failures, swap in --intake insurance and let the preset fill the merchant name, suite name, scenario id, and scenario title unless you need to override them.

Insurance shortcut:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --intake insurance \
  --out voice-testops/insurance-suite.json \
  --merchant-out voice-testops/insurance-merchant.json

For outbound sales or lead-generation recordings, the risky turn may be on the agent side instead of the customer side. Sanitize recording URLs and file names first, then generate turns from assistant lines:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --turn-role assistant \
  --out voice-testops/outbound-suite.json \
  --merchant-name "Outbound lead generation" \
  --scenario-id "outbound_wechat_followup"

Need the suite as data instead of files? Print clean JSON to stdout and pipe it into whatever comes next:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --print-json \
  --merchant-name "Lumen Portrait Studio" | jq '.scenarios[0].turns | length'

--print-json keeps stdout machine-readable and does not write suite or merchant files. It is handy for CI glue, jq, or redirecting a reviewed draft into your own generator.

Prefer a transcript file? Use --input:

npx voice-agent-testops from-transcript \
  --input examples/voice-testops/transcripts/failed-photo-booking.txt \
  --out examples/voice-testops/generated-transcript-suite.json \
  --merchant-name "Lumen Portrait Studio" \
  --name "Generated transcript regression" \
  --source website

Already have a suite? Add the new failure as another scenario:

pbpaste | npx voice-agent-testops from-transcript \
  --stdin \
  --out voice-testops/suite.json \
  --append \
  --preview \
  --merchant-out voice-testops/merchants/failed-call.json \
  --merchant-name "Lumen Portrait Studio" \
  --scenario-id "missed_booking_handoff" \
  --scenario-title "Missed booking handoff"

Drop --preview from the append command when you are ready to modify the suite.

The generator is deterministic. It does not call an LLM; it extracts customer turns by default, or assistant turns with --turn-role assistant, infers a draft merchant profile when you do not have one yet, and adds reviewable assertions for unsafe promises, pricing facts, lead fields, handoff intent, and latency. Treat the generated files as a first draft, then tighten them before using the suite as a release gate.

If you already keep approved business facts in JSON, add --merchant examples/voice-testops/merchants/guangying-photo.json. That gives the generated suite better price and service assertions from day one.

Draft Regressions From Failed Reports

After a run fails, turn the failed turns back into reviewable regression artifacts:

npx voice-agent-testops draft-regressions \
  --report .voice-testops/report.json \
  --suite voice-testops/suite.json \
  --out voice-testops/regression-draft.json \
  --clusters .voice-testops/failure-clusters.md

regression-draft.json keeps the failed scenarios and the turns needed to reproduce them. failure-clusters.md groups failures by severity, assertion code, and message fingerprint, so a team can review one cluster at a time instead of rereading every transcript. Treat both files as drafts: tighten the generated suite, then append the approved cases to your baseline gate.

Import Production Calls For Sampling

When you have exported production or pilot calls, create a deterministic review sample:

npx voice-agent-testops import-calls \
  --input examples/voice-testops/production-calls/sample-calls.jsonl \
  --out .voice-testops/call-sample.json \
  --summary .voice-testops/call-sampling.md \
  --transcripts .voice-testops/call-transcripts \
  --sample-size 20 \
  --seed weekly-2026-05-07

call-sample.json is the automation manifest. call-sampling.md is for weekly human review. call-transcripts contains labeled text files that can be passed into from-transcript when a sampled call should become a regression test. Add --risk-only when you only want calls with inferred risk tags such as handoff requests, pricing questions, shared lead info, unsupported promises, or long conversations.

Triage Recording Intake

When the input is a private manifest of raw recording links, validate the manifest before transcribing the batch:

npx voice-agent-testops recording-intake \
  --input .voice-testops/recordings/recording-intake.csv \
  --summary .voice-testops/recordings/intake-summary.md

The input can be the full manifest template or a one-URL-per-line private recording list. Raw URL lists are normalized conservatively as maybe, pii, consent_status=unknown, and regression_candidate=no until a human reviews them. The summary groups keep / maybe / discard, business_type, risk_tag, quality, and turn_role_hint, then lists regression_candidate=yes rows that are ready for the next step. audio_url_private is never printed in the summary; real URLs, missing fields, invalid enums, and consent/quality conflicts are reported as issue rows.

Calibrate Semantic Judge

Run the public seed set back through the local judge to generate an agreement report by industry and rubric:

npx voice-agent-testops calibrate-judge \
  --out .voice-testops/semantic-judge-calibration.md \
  --json .voice-testops/semantic-judge-calibration.json

Add --fail-on-disagreement when using the seed as a release gate.

Create Pilot Deliverables

After a test run, generate customer-facing pilot artifacts from the JSON report:

npx voice-agent-testops pilot-report \
  --report .voice-testops/report.json \
  --commercial .voice-testops/commercial-report.md \
  --recap .voice-testops/pilot-recap.md \
  --customer "Anju Realty" \
  --period "Pilot week 1"

commercial-report.md summarizes launch readiness, severity breakdown, evidence links, and next pilot steps. pilot-recap.md is a meeting template for decisions, action owners, and regression assets to add next.

When you need a short GitHub/email/Discord follow-up instead of a full report, generate a proof card from the same JSON report:

npx voice-agent-testops proof-card \
  --report .voice-testops/report.json \
  --out .voice-testops/proof-card.md \
  --customer "Anju Realty" \
  --period "Pilot week 1" \
  --proof-url "https://example.com/report.html"

proof-card.md is intentionally short: coverage, pass/fail status, severity counts, the top failed turns, a minimum next-step ask, and the privacy boundary. It is designed for outreach after a public-safe demo or transcript-only trial.

Suite Format

Suites are just JSON. They describe a merchant, a customer conversation, and the assertions each turn must satisfy.

{
  "name": "Photo studio launch check",
  "scenarios": [
    {
      "id": "pricing",
      "title": "Customer asks for price",
      "source": "website",
      "merchant": {
        "name": "光影写真馆",
        "slug": "guangying-photo",
        "industry": "photography",
        "address": "上海市徐汇区示例路 88 号",
        "serviceArea": "上海市区",
        "businessHours": "10:00-21:00",
        "contactPhone": "13800000000",
        "packages": [
          {
            "name": "单人写真",
            "priceRange": "599-1299 元",
            "includes": "服装 2 套，精修 9 张",
            "bestFor": "个人写真"
          }
        ],
        "faqs": [],
        "bookingRules": {
          "requiresManualConfirm": true,
          "requiredFields": ["name", "phone"]
        }
      },
      "turns": [
        {
          "user": "单人写真多少钱，能保证拍得好看吗",
          "expect": [
            { "type": "must_contain_any", "phrases": ["599", "1299"] },
            { "type": "must_not_match", "pattern": "最低价|百分百|保证拍得好看" },
            { "type": "lead_intent", "intent": "pricing" },
            { "type": "max_latency_ms", "value": 25000 }
          ]
        }
      ]
    }
  ]
}

You can also keep merchant profiles in separate files and reference them with merchantRef, as shown in examples/voice-testops/photo-studio-multiturn-suite.json.

Assertions

Assertion	Purpose
`must_contain_any`	Require at least one expected phrase in the spoken answer; Chinese matching normalizes common Simplified/Traditional ASR drift
`must_not_match`	Block forbidden regex patterns such as absolute promises; Chinese matching also checks a normalized Simplified/Traditional copy
`max_latency_ms`	Fail turns that exceed a latency threshold
`lead_field_present`	Require structured lead fields such as `phone`
`lead_intent`	Require the summary intent to match the scenario
`semantic_judge`	Evaluate higher-level business rubrics such as unsupported guarantees or required handoff
`tool_called`	Require a returned tool/function call, optionally with a matching argument subset
`backend_state_present`	Require a path to exist in the returned backend `state` snapshot
`backend_state_equals`	Require a backend `state` path to equal an expected JSON value
`audio_replay_present`	Require a returned replay URL so reviewers can listen to the failed or sampled turn
`voice_metric_max`	Require a returned voice metric to stay at or below a threshold
`voice_metric_min`	Require a returned voice metric to stay at or above a threshold

For tool_called and backend-state assertions, your test bridge should return optional tools and state fields in addition to spoken and summary. This is useful when the spoken answer is correct but the agent forgot to create a lead, update CRM state, draft a booking, or mark a handoff. For audio and voice-metric assertions, return optional audio and voiceMetrics fields from the bridge. This catches voice-specific failures like slow time-to-first-word, long silence, low ASR confidence, or missing replay evidence even when the text transcript looks acceptable.

CI

The repository includes a GitHub Actions workflow at .github/workflows/voice-testops.yml. It runs unit tests, demo suites, production build, high-severity audit, and uploads generated reports as artifacts.

For a real HTTP agent, generate a ready-to-edit GitHub Actions workflow and keep the endpoint in a GitHub Secret:

npx voice-agent-testops init \
  --stack http \
  --with-ci \
  --endpoint-env VOICE_AGENT_ENDPOINT

Add VOICE_AGENT_ENDPOINT as a GitHub Secret, pointing at your test-turn bridge. The generated workflow validates the suite, runs doctor --agent http against --suite voice-testops/suite.json, then runs the regression suite with CI-friendly outputs:

It also runs the semantic judge seed calibration as a release gate:

npx voice-agent-testops calibrate-judge \
  --out .voice-testops/semantic-judge-calibration.md \
  --json .voice-testops/semantic-judge-calibration.json \
  --fail-on-disagreement

npx voice-agent-testops run \
  --agent http \
  --endpoint "$VOICE_AGENT_ENDPOINT" \
  --suite voice-testops/suite.json \
  --summary .voice-testops/summary.md \
  --junit .voice-testops/junit.xml \
  --fail-on-severity critical

When a previous report is available, compare the current run against it:

npx voice-agent-testops run \
  --suite voice-testops/suite.json \
  --baseline .voice-testops-baseline/report.json \
  --diff-markdown .voice-testops/diff.md \
  --fail-on-new \
  --fail-on-severity critical

You can also compare two saved JSON reports without rerunning the suite:

npx voice-agent-testops compare \
  --baseline .voice-testops-baseline/report.json \
  --current .voice-testops/report.json \
  --diff-markdown .voice-testops/diff.md \
  --fail-on-new \
  --fail-on-severity critical

The generated workflow caches the latest push report as .voice-testops-baseline/report.json. On the first run it gates on current critical failures. On later runs it switches to --fail-on-new --fail-on-severity critical, so newly introduced critical failures block release while new minor or major drift remains visible in .voice-testops/diff.md. The diff lists new, resolved, and unchanged failures, then appends .voice-testops/summary.md, .voice-testops/diff.md, and .voice-testops/semantic-judge-calibration.md to GITHUB_STEP_SUMMARY. It also uploads .voice-testops/report.json, .voice-testops/report.html, .voice-testops/summary.md, .voice-testops/junit.xml, .voice-testops/diff.md, .voice-testops/semantic-judge-calibration.md, and .voice-testops/semantic-judge-calibration.json through actions/upload-artifact.

Use --fail-on-severity when you want CI to block only the failures that matter for release. This keeps minor copy drift visible in the report without treating it like a production-stopping safety issue.

npx voice-agent-testops run \
  --suite examples/voice-testops/chinese-risk-suite.json \
  --fail-on-severity critical

Useful commands:

npm test
npm run build
npm audit --audit-level=high

Roadmap

Voice Agent TestOps is intentionally small today. The next useful steps are based on real agent feedback:

More adapters for realtime voice stacks
A larger public library of risky business scenarios
CI gates that can fail a deployment when agent behavior regresses
Report diffs across model, prompt, and workflow changes
More transcript import helpers for turning real calls into regression suites

If your team has ever watched a voice agent sound confident at exactly the wrong moment, star the repo and try it against one real endpoint.

Name		Name	Last commit message	Last commit date
Latest commit History 121 Commits
.github		.github
bin		bin
docs		docs
examples		examples
prisma		prisma
scripts		scripts
src		src
tests		tests
.env.example		.env.example
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
README.zh-CN.md		README.zh-CN.md
compose.yaml		compose.yaml
next.config.mjs		next.config.mjs
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts

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Voice Agent TestOps

Why This Exists

What It Catches

Quick Start

Example Library

Create Mock Data

Editor Autocomplete

Connect An Agent

Generic HTTP Agent

OpenClaw-compatible Endpoint

SIP Voice Agents

Integration Guides

Sales Demo

Turn A Real Failure Into A Regression Test

Draft Regressions From Failed Reports

Import Production Calls For Sampling

Triage Recording Intake

Calibrate Semantic Judge

Create Pilot Deliverables

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Voice Agent TestOps

Why This Exists

What It Catches

Quick Start

Example Library

Create Mock Data

Editor Autocomplete

Connect An Agent

Generic HTTP Agent

OpenClaw-compatible Endpoint

SIP Voice Agents

Integration Guides

Sales Demo

Turn A Real Failure Into A Regression Test

Draft Regressions From Failed Reports

Import Production Calls For Sampling

Triage Recording Intake

Calibrate Semantic Judge

Create Pilot Deliverables

Suite Format

Assertions

CI

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