Openclaw QA Testing

OpenClaw QA Testing

Use this skill for qa-lab / qa-channel work. Repo-local QA only.

Read first

• docs/concepts/qa-e2e-automation.md
• docs/help/testing.md
• docs/channels/qa-channel.md
• qa/README.md
• qa/scenarios/index.yaml
• extensions/qa-lab/src/suite.ts
• extensions/qa-lab/src/character-eval.ts

Model policy

• Live OpenAI lane: openai/gpt-5.4
• Fast mode: on
• Do not use:
  • openai/gpt-5.4-pro
  • openai/gpt-5.4-mini
• Only change model policy if the user explicitly asks.

Default workflow

1. Read the scenario pack and current suite implementation.
2. Decide lane:
   • mock/dev: mock-openai
   • real validation: live-frontier
3. For live OpenAI, use:

OPENCLAW_LIVE_OPENAI_KEY="${OPENAI_API_KEY}" \
pnpm openclaw qa suite \
  --provider-mode live-frontier \
  --model openai/gpt-5.4 \
  --alt-model openai/gpt-5.4 \
  --output-dir .artifacts/qa-e2e/run-all-live-frontier-<tag>

4. Watch outputs:
   • summary: .artifacts/qa-e2e/run-all-live-frontier-<tag>/qa-suite-summary.json
   • report: .artifacts/qa-e2e/run-all-live-frontier-<tag>/qa-suite-report.md
5. If the user wants to watch the live UI, find the current openclaw-qa listen port and report http://127.0.0.1:<port>.
6. If a scenario fails, fix the product or harness root cause, then rerun the full lane.

OTEL smoke

For local QA-lab OpenTelemetry validation, use:

pnpm qa:otel:smoke

This starts a local OTLP/HTTP trace receiver, runs the otel-trace-smoke scenario through qa-channel, decodes the emitted protobuf spans, and verifies the exported trace names and privacy contract. It does not require Opik, Langfuse, or external collector credentials.

QA credentials and 1Password

• Use op only inside tmux for QA secret lookup in this repo.
• Quick auth check inside tmux:

op account list

• Direct Telegram npm live test secrets currently live in 1Password item:
  • vault: OpenClaw
  • item: Telegram E2E
• That item is the first place to look for:
  • OPENCLAW_QA_TELEGRAM_DRIVER_BOT_TOKEN
  • OPENCLAW_QA_TELEGRAM_SUT_BOT_TOKEN
  • OPENCLAW_QA_PROVIDER_MODE
  • OPENCLAW_NPM_TELEGRAM_PACKAGE_SPEC
• Convex QA secrets currently live in 1Password items:
  • vault: OpenClaw
  • item: OPENCLAW_QA_CONVEX_SITE_URL
  • item: OPENCLAW_QA_CONVEX_SECRET_MAINTAINER
  • item: OPENCLAW_QA_CONVEX_SECRET_CI
• Additional related notes/login items seen during QA credential work:
  • vault: Private
  • items: OPENCLAW QA, Convex, Telegram
• If a required value is missing from those notes:
  • do not guess
  • ask the maintainer/operator for the current value or the current 1Password item name
  • for Telegram direct runs, OPENCLAW_QA_TELEGRAM_GROUP_ID may be stored separately from Telegram E2E
  • for Convex runs, the leased Telegram credential should provide the Telegram group id and bot tokens together; do not require a separate OPENCLAW_QA_TELEGRAM_GROUP_ID
  • for Convex runs, prefer OpenClaw/OPENCLAW_QA_CONVEX_SITE_URL; if that is stale or unclear, ask for the active pool URL before running
• Prefer direct Telegram envs for the npm Telegram Docker lane when available:

OPENCLAW_QA_TELEGRAM_GROUP_ID="..." \
OPENCLAW_QA_TELEGRAM_DRIVER_BOT_TOKEN="..." \
OPENCLAW_QA_TELEGRAM_SUT_BOT_TOKEN="..." \
OPENCLAW_QA_PROVIDER_MODE="mock-openai" \
OPENCLAW_NPM_TELEGRAM_PACKAGE_SPEC="openclaw@beta" \
pnpm test:docker:npm-telegram-live

• Prefer Convex mode when the goal is stable shared QA infra:
  • round-robin credential leasing
  • thinner wrapper for channel-specific setup
  • CLI/admin flows around the pooled credentials
• Live npm Telegram Docker lane note:
  • scripts/e2e/npm-telegram-live-runner.ts reads OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE
  • do not assume OPENCLAW_QA_PROVIDER_MODE is consumed by that wrapper
  • if a 1Password note only gives OPENCLAW_QA_PROVIDER_MODE, map it explicitly to OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE before running the Docker lane
• Verified live shape:
  • Convex mode can pass the real Docker lane without direct Telegram env vars
  • leased Telegram payload includes the group id coupled to the driver/SUT tokens
  • a real run of pnpm test:docker:npm-telegram-live passed with:
    • OPENCLAW_QA_CREDENTIAL_SOURCE=convex
    • OPENCLAW_QA_CREDENTIAL_ROLE=maintainer
    • OPENCLAW_QA_CONVEX_SITE_URL
    • OPENCLAW_QA_CONVEX_SECRET_MAINTAINER
    • OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE=mock-openai
• If direct Telegram env is missing locally and op signin blocks, prefer dispatching the manual GitHub lane because the qa-live-shared environment already has Convex CI credentials:

gh workflow run "NPM Telegram Beta E2E" --repo openclaw/openclaw --ref main \
  -f package_spec=openclaw@YYYY.M.D-beta.N \
  -f package_label=openclaw@YYYY.M.D-beta.N \
  -f provider_mode=mock-openai

• Poll the exact run id from the dispatch URL. gh run view --json artifacts is not supported; list artifacts with:

gh api repos/openclaw/openclaw/actions/runs/<run-id>/artifacts

WhatsApp live credentials

Use this when setting up or replacing Convex kind=whatsapp credentials.

• Treat WhatsApp QA credentials as operator-owned live accounts, not generated fixtures.
• Use two dedicated WhatsApp-capable test numbers: one driver account and one SUT account. Do not use personal numbers or personal OpenClaw WhatsApp accounts in the shared pool.
• Register and link each account manually with WhatsApp or WhatsApp Business, storing Web auth only in isolated local auth dirs outside the repo.
• For group coverage, create a dedicated test group that includes both QA accounts and store its JID as groupJid; otherwise the group mention-gating scenario should be skipped by default and fail when explicitly requested.
• Package the two Baileys auth dirs into base64 .tgz payload fields and add a new active Convex credential row. Prefer adding a fresh row and disabling stale/broken rows over overwriting credentials in place.
• Expected payload fields: driverPhoneE164, sutPhoneE164, driverAuthArchiveBase64, sutAuthArchiveBase64, and optional groupJid.
• Keep credential material out of the repo, logs, PRs, and screenshots. Redact phone numbers unless the operator explicitly asks for local debugging.
• Validate with pnpm openclaw qa whatsapp --credential-source convex --credential-role maintainer --provider-mode mock-openai and preserve artifact paths plus redacted pass/fail summaries.
• If WhatsApp expires or invalidates a linked Web session, relink locally, package fresh auth archives, add a new Convex row, then disable the stale row.

Character evals

Use qa character-eval for style/persona/vibe checks across multiple live models.

pnpm openclaw qa character-eval \
  --model openai/gpt-5.4,thinking=xhigh \
  --model openai/gpt-5.2,thinking=xhigh \
  --model openai/gpt-5,thinking=xhigh \
  --model anthropic/claude-opus-4-6,thinking=high \
  --model anthropic/claude-sonnet-4-6,thinking=high \
  --model zai/glm-5.1,thinking=high \
  --model moonshot/kimi-k2.5,thinking=high \
  --model google/gemini-3.1-pro-preview,thinking=high \
  --judge-model openai/gpt-5.4,thinking=xhigh,fast \
  --judge-model anthropic/claude-opus-4-6,thinking=high \
  --concurrency 16 \
  --judge-concurrency 16 \
  --output-dir .artifacts/qa-e2e/character-eval-<tag>

• Runs local QA gateway child processes, not Docker.
• Preferred model spec syntax is provider/model,thinking=<level>[,fast|,no-fast|,fast=<bool>] for both --model and --judge-model.
• Do not add new examples with separate --model-thinking; keep that flag as legacy compatibility only.
• Defaults to candidate models openai/gpt-5.4, openai/gpt-5.2, openai/gpt-5, anthropic/claude-opus-4-6, anthropic/claude-sonnet-4-6, zai/glm-5.1, moonshot/kimi-k2.5, and google/gemini-3.1-pro-preview when no --model is passed.
• Candidate thinking defaults to high, with xhigh for OpenAI models that support it. Prefer inline --model provider/model,thinking=<level>; --thinking <level> and --model-thinking <provider/model=level> remain compatibility shims.
• OpenAI candidate refs default to fast mode so priority processing is used where supported. Use inline ,fast, ,no-fast, or ,fast=false for one model; use --fast only to force fast mode for every candidate.
• Judges default to openai/gpt-5.4,thinking=xhigh,fast and anthropic/claude-opus-4-6,thinking=high.
• Report includes judge ranking, run stats, durations, and full transcripts; do not include raw judge replies. Duration is benchmark context, not a grading signal.
• Candidate and judge concurrency default to 16. Use --concurrency <n> and --judge-concurrency <n> to override when local gateways or provider limits need a gentler lane.
• Scenario source is YAML-only under qa/scenarios/: use index.yaml and per-scenario *.yaml files with top-level title, scenario, and optional flow. Never add fenced qa-scenario / qa-flow Markdown files.
• For isolated character/persona evals, write the persona into SOUL.md and blank IDENTITY.md in the scenario flow. Use SOUL.md + IDENTITY.md only when intentionally testing how the normal OpenClaw identity combines with the character.
• Keep prompts natural and task-shaped. The candidate model should receive character setup through SOUL.md, then normal user turns such as chat, workspace help, and small file tasks; do not ask "how would you react?" or tell the model it is in an eval.
• Prefer at least one real task, such as creating or editing a tiny workspace artifact, so the transcript captures character under normal tool use instead of pure roleplay.

Codex CLI model lane

Use model refs shaped like codex-cli/<codex-model> whenever QA should exercise Codex as a model backend.

Examples:

pnpm openclaw qa suite \
  --provider-mode live-frontier \
  --model codex-cli/<codex-model> \
  --alt-model codex-cli/<codex-model> \
  --scenario <scenario-id> \
  --output-dir .artifacts/qa-e2e/codex-<tag>

pnpm openclaw qa manual \
  --model codex-cli/<codex-model> \
  --message "Reply exactly: CODEX_OK"

• Treat the concrete Codex model name as user/config input; do not hardcode it in source, docs examples, or scenarios.
• Live QA preserves CODEX_HOME so Codex CLI auth/config works while keeping HOME and OPENCLAW_HOME sandboxed.
• Mock QA should scrub CODEX_HOME.
• If Codex returns fallback/auth text every turn, first check CODEX_HOME, relevant secret-backed auth, and gateway child logs before changing scenario assertions.
• For model comparison, include codex-cli/<codex-model> as another candidate in qa character-eval; the report should label it as an opaque model name.

Repo facts

• Seed scenarios live in qa/scenarios/index.yaml and qa/scenarios/<theme>/*.yaml.
• Main live runner: extensions/qa-lab/src/suite.ts
• QA lab server: extensions/qa-lab/src/lab-server.ts
• Child gateway harness: extensions/qa-lab/src/gateway-child.ts
• Synthetic channel: extensions/qa-channel/

What “done” looks like

• Full suite green for the requested lane.
• User gets:
  • watch URL if applicable
  • pass/fail counts
  • artifact paths
  • concise note on what was fixed

Common failure patterns

• Live timeout too short:
  • widen live waits in extensions/qa-lab/src/suite.ts
• Discovery cannot find repo files:
  • point prompts at repo/... inside seeded workspace
• Subagent proof too brittle:
  • prefer stable final reply evidence over transient child-session listing
• Harness “rebuild” delay:
  • dirty tree can trigger a pre-run build; expect that before ports appear

When adding scenarios

• Add or update scenario YAML under qa/scenarios/; do not add .md scenario files or fenced YAML blocks.
• Keep kickoff expectations in qa/scenarios/index.yaml aligned
• Add executable coverage in extensions/qa-lab/src/suite.ts
• Prefer end-to-end assertions over mock-only checks
• Save outputs under .artifacts/qa-e2e/