Executes defined quality gates and maps technical results to project acceptance criteria.
Install
mkdir -p .claude/skills/verify-datashaman && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13161" && unzip -o skill.zip -d .claude/skills/verify-datashaman && rm skill.zipInstalls to .claude/skills/verify-datashaman
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
-- | ---------------------------------------------------------------------------------------------------------------- | | Lint | `npm run lint`, `ruff check`, `php -d detect_unicode=0 $(which php-cs-fixer) fix --dry-run`, `golangci-lint run` | | Types | `npm run typecheck`, `tscKey capabilities
- →Run automated quality gates like linting and type checking
- →Execute project-defined tests
- →Map test results to spec acceptance criteria
- →Generate a `verification_report.json` with evidence and severities
- →Identify acceptance criteria without evidence
How it works
This skill executes automated quality gates and project tests, then maps their results to acceptance criteria defined in `spec.json`. It generates a report with findings categorized by severity.
Inputs & outputs
When to use verify
- →Run quality gates
- →Verify acceptance criteria
- →Validate build status
- →Generate compliance reports
About this skill
-- | ---------------------------------------------------------------------------------------------------------------- |
| Lint | npm run lint, ruff check, php -d detect_unicode=0 $(which php-cs-fixer) fix --dry-run, golangci-lint run |
| Types | npm run typecheck, tsc --noEmit, phpstan, mypy |
| Tests | npm test, php artisan test, pytest -q, go test ./... |
Record in verification_report.json → checks: pass | fail | not_run (only use not_run if the project truly has no check; say why in a finding).
Part B — Spec coverage matrix
- Open
spec.json→acceptance_criteria. - For each AC id, list evidence:
- test name + file, or
- manual repro steps + screenshot/log (if no test yet—flag as risk).
- Any AC with no evidence → finding (usually high until tests exist for must-have behavior).
Part C — Severity rubric (use in every finding)
| Level | Meaning | Example |
|---|---|---|
| critical | Security hole, data loss, auth bypass, payment wrong | Missing auth check on mutating route |
| high | Wrong behavior vs spec, crash on main path, CI red | AC fails, 500 on happy path |
| medium | Edge case, flaky test, incomplete error handling | Wrong message body, race in rare case |
| low | Polish, copy, minor a11y | Typo in validation message |
Every finding needs **owner** (team or role), **impact**, **evidence**, **remediation**.
Output
verification_report.json:status,build_ref,checks,findings,metadata(see schema).
Anti-patterns
- “Looks fine” without AC → evidence mapping.
- Downgrading high to please schedule—severity describes user/system risk, not comfort.
When not to use it
- →When a pass/fail tied to evidence is not needed
- →When only a gut feeling assessment is sufficient
- →When the project truly has no checks to run
Limitations
- →Requires a `spec.json` file with acceptance criteria
- →Every finding needs `owner`, `impact`, `evidence`, `remediation`
- →Severity describes user/system risk, not comfort
How it compares
This skill provides a formal, evidence-based verification process by mapping automated test results to specific acceptance criteria and generating a structured report, which is more rigorous than simple pass/fail testing.
Compared to similar skills
verify side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| verify (this skill) | 0 | 4mo | No flags | Intermediate |
| e2e-testing-patterns | 8 | 2mo | No flags | Intermediate |
| testing-workflow | 16 | 9mo | Review | Intermediate |
| perf-lighthouse | 13 | 5mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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