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chore: initial agent team setup
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skills/qa-checklist.md
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skills/qa-checklist.md
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---
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name: qa-checklist
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description: Self-validation checklist. All workers run this against their own output before returning results.
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---
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## Self-QA checklist
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Before returning your output, validate against every item below. If you find a violation, fix it — don't just note it.
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### Factual accuracy
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- Every file path, function name, class name, and line number you reference — does it actually exist? Verify with Read/Grep if uncertain. Never guess paths or signatures.
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- Every version number, API endpoint, or external reference — is it correct? If you can't verify, say "unverified" explicitly.
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- No invented specifics. If you don't know something, say so.
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### Logic and correctness
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- Do your conclusions follow from the evidence? Trace the reasoning.
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- Are there internal contradictions in your output?
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- No vague hedging masking uncertainty — "should work" and "probably fine" are not acceptable. Be precise about what you know and don't know.
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### Scope and completeness
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- Re-read the acceptance criteria. Check each one explicitly. Did you address all of them?
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- Did you solve the right problem? It's possible to produce clean, correct output that doesn't answer what was asked.
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- Are there required parts missing?
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### Security and correctness risks (code output)
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- No unsanitized external input at system boundaries
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- No hardcoded secrets or credentials
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- No command injection, path traversal, or SQL injection vectors
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- Error handling present where failures are possible
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- No silent failure — errors propagate or are logged
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### Code quality (code output)
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- Matches the project's existing patterns and style
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- No unrequested additions, refactors, or "improvements"
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- No duplicated logic that could use an existing helper
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- Names are descriptive, no magic numbers
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### Claims and assertions
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- If you stated something as fact, can you back it up? Challenge your own claims.
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- If you referenced documentation or source code, did you actually read it or are you recalling from training data? When it matters, verify.
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## After validation
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In your Self-Assessment section, include:
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- `QA self-check: [pass/fail]` — did your output survive the checklist?
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- If fail: what you found and fixed before submission
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- If anything remains unverifiable, flag it explicitly as `Unverified: [claim]`
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