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ufukyuksel-devufukyuksel-dev/SUPER_COMPUTER_AI/skills/ai-engineering/implementation-verification/SKILL.md

implementation-verification

Skill0 starsChanged 47 days agoMITView on GitHub

Use when a task is claimed complete — before reporting success. Exercises the deliverable end-to-end against its acceptance criteria: run it, probe edge cases, check claims against actual output, list what was NOT verified. Do NOT use for designing metrics (see skill eval-harness).

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 10 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈10

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Verify an existing deliverable against authoritative acceptance criteria with direct execution and observed evidence.

    line 10
  2. Distinctive:

    Do not design a future architecture or implementation plan.

    line 11
  3. Distinctive:

    Do not invent metrics, evaluation sets, or judges.

    line 12
  4. Distinctive:

    Treat code inspection, diffs, unit tests, manifests, and green checks as supporting evidence only for the scope they actually exercise.

    line 13
  5. Distinctive:

    Never redefine, narrow, waive, or convert an acceptance criterion into a weaker pass without explicit human approval.

    line 14
  6. Distinctive:

    Run unit, integration, regression, static, security, and evaluation checks that map to criteria.

    line 23
  7. Distinctive:

    Read the verification checklist before sign-off.

    line 28
  8. Distinctive:

    Use the least-privileged representative environment.

    line 41
  9. Very specific:

    If execution permission is unavailable, provide inspection findings and exact commands but label the execution-dependent criteria …

    line 42
  10. Very specific:

    If an external provider is down or credentials are unavailable, never simulate success or fake output.

    line 43
  11. Distinctive:

    If required observability or side-effect inspection is unavailable, do not pass a criterion solely from an exit code or response body.

    line 44
  12. Distinctive:

    If a check would expose secrets or confidential payloads, redact evidence or use an approved safe fixture without weakening the behavior …

    line 45

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Implementation Verification

Boundaries

  • Verify an existing deliverable against authoritative acceptance criteria with direct execution and observed evidence.
  • Do not design a future architecture or implementation plan; for that work, see skill ai-system-design.
  • Do not invent metrics, evaluation sets, or judges; for evaluation design, see skill eval-harness and consume its declared gates.
  • Treat code inspection, diffs, unit tests, manifests, and green checks as supporting evidence only for the scope they actually exercise.
  • Never redefine, narrow, waive, or convert an acceptance criterion into a weaker pass without explicit human approval.

Decision Workflow

  1. Establish the exact deliverable, environment, claimed completion scope, authoritative criteria, required side effects, prohibited side effects, and risk boundaries. Reject vague success criteria before sign-off.
  2. Build an evidence matrix with one row per criterion: criterion, scope, direct command/probe, expected observable result, actual output/side effect, artifact locator, and PASS/FAIL/UNVERIFIED status.
  3. Inspect the current implementation and environment narrowly enough to choose valid execution paths. Record versions, configuration, fixtures, credentials/permissions availability, and preconditions; redact secrets from evidence.
  4. Execute the real entry point end to end in the safest representative environment. Capture the exact command or request, exit/status, relevant output, logs, generated artifacts, state changes, and cleanup/rollback result.
  5. Exercise relevant edge and failure behavior: malformed and boundary inputs, empty/large cases, authorization and tenant isolation, retries/timeouts, idempotency, concurrency, partial dependency failure, cancellation, rollback, and recovery.
  6. Run unit, integration, regression, static, security, and evaluation checks that map to criteria. Preserve their scope; unit success does not prove integration or end-to-end acceptance.
  7. Reconcile claims against observed behavior. Distinguish product failures, test defects, and infrastructure limitations without turning any of them into a pass.
  8. Exhaust safe local evidence when an external dependency is unavailable. Test adapters, request construction, validation, deterministic failure handling, and recorded fixtures where valid, but mark the live provider-dependent path UNVERIFIED.
  9. Sign off only when every required criterion has direct, scope-matched passing evidence and no required path remains unverified. Otherwise report incomplete status, exact failures/gaps, residual risk, and next verification command.

Read the verification checklist before sign-off.

Evidence Status Rules

  • PASS: the required path ran, the expected observable result and side effects occurred, and evidence covers the criterion's full scope.
  • FAIL: observed product behavior contradicts the criterion, including unsafe or prohibited side effects.
  • UNVERIFIED: evidence is inaccessible, skipped, simulated, stale, indirect, or narrower than the criterion. UNVERIFIED is not a weak pass.

Report exact commands/probes, observed outputs, failures, skipped checks, inaccessible dependencies, unverified claims, and residual risk. Keep raw artifacts available or identify their path.

Tool Requirements & Degradation

  • Require repository/artifact inspection plus permission to run the build, tests, actual entry point, relevant service/dependency probes, log/state inspection, and safe cleanup.
  • Use the least-privileged representative environment. Ask before irreversible actions, production writes, requirement-weakening workarounds, or a paid full behavior suite.
  • If execution permission is unavailable, provide inspection findings and exact commands but label the execution-dependent criteria UNVERIFIED.
  • If an external provider is down or credentials are unavailable, never simulate success or fake output. Exhaust safe local evidence, separate the infrastructure limitation, and mark the live path UNVERIFIED.
  • If required observability or side-effect inspection is unavailable, do not pass a criterion solely from an exit code or response body.
  • If a check would expose secrets or confidential payloads, redact evidence or use an approved safe fixture without weakening the behavior being tested.

Failure Modes

  • Approving from a code diff, review, manifest, typecheck, or unit suite without running the deliverable.
  • Testing only the happy path and omitting malformed input, authorization, retries, partial failure, or side effects.
  • Using a mock, fixture, or simulated provider result as proof of the live integration.
  • Hiding skipped checks, truncated output, flaky results, environment drift, or inaccessible evidence.
  • Treating infrastructure failure as product success or product failure without distinguishing the evidence.
  • Claiming a broad criterion from a narrow test or assuming a green command covers undocumented scope.
  • Moving the acceptance threshold after observing results or redefining completion around what already passes.

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