
evidence-verification
by yonatangross
The Complete AI Development Toolkit for Claude Code — 159 skills, 34 agents, 20 commands, 144 hooks. Production-ready patterns for FastAPI, React 19, LangGraph, security, and testing.
SKILL.md
Evidence Verification
name: evidence-verification description: Use when completing tasks, code reviews, or deployments to verify work with evidence. Collects test results, build outputs, coverage metrics, and exit codes to prove work is complete. version: 2.0.0 author: OrchestKit AI Agent Hub tags: [quality, verification, testing, evidence, completion] context: fork agent: code-quality-reviewer allowed-tools:
- Read
- Grep
- Glob
- Bash # For running tests and capturing evidence This skill teaches agents how to collect and verify evidence before marking tasks complete. Inspired by production-grade development practices, it ensures all claims are backed by executable proof: test results, coverage metrics, build success, and deployment verification.
Key Principle: Show, don't tell. No task is complete without verifiable evidence. user-invocable: false
Evidence Verification
Overview
Auto-Activate Triggers
- Completing code implementation
- Finishing code review
- Marking tasks complete in Squad mode
- Before agent handoff
- Production deployment verification
Manual Activation
- When user requests "verify this works"
- Before creating pull requests
- During quality assurance reviews
- When troubleshooting failures
Evidence Verification
Core Concepts
1. Evidence Types
Test Evidence
- Exit code (must be 0 for success)
- Test suite results (passed/failed/skipped)
- Coverage percentage (if available)
- Test duration
Build Evidence
- Build exit code (0 = success)
- Compilation errors/warnings
- Build artifacts created
- Build duration
Deployment Evidence
- Deployment status (success/failed)
- Environment deployed to
- Health check results
- Rollback capability verified
Code Quality Evidence
- Linter results (errors/warnings)
- Type checker results
- Security scan results
- Accessibility audit results
2. Evidence Collection Protocol
## Evidence Collection Steps
1. **Identify Verification Points**
- What needs to be proven?
- What could go wrong?
- What does "complete" mean?
2. **Execute Verification**
- Run tests
- Run build
- Run linters
- Check deployments
3. **Capture Results**
- Record exit codes
- Save output snippets
- Note timestamps
- Document environment
4. **Store Evidence**
- Add to shared context
- Reference in task completion
- Link to artifacts
3. Verification Standards
Minimum Evidence Requirements:
- ✅ At least ONE verification type executed
- ✅ Exit code captured (0 = pass, non-zero = fail)
- ✅ Timestamp recorded
- ✅ Evidence stored in context
Production-Grade Requirements:
- ✅ Tests run with exit code 0
- ✅ Coverage >70% (or project standard)
- ✅ Build succeeds with exit code 0
- ✅ No critical linter errors
- ✅ Security scan passes
Evidence Verification
Evidence Collection Templates
Template 1: Test Evidence
Use this template when running tests:
## Test Evidence
**Command:** `npm test` (or equivalent)
**Exit Code:** 0 ✅ / non-zero ❌
**Duration:** X seconds
**Results:**
- Tests passed: X
- Tests failed: X
- Tests skipped: X
- Coverage: X%
**Output Snippet:**
[First 10 lines of test output]
**Timestamp:** YYYY-MM-DD HH:MM:SS
**Environment:** Node vX.X.X, OS, etc.
Template 2: Build Evidence
Use this template when building:
## Build Evidence
**Command:** `npm run build` (or equivalent)
**Exit Code:** 0 ✅ / non-zero ❌
**Duration:** X seconds
**Artifacts Created:**
- dist/bundle.js (245 KB)
- dist/styles.css (18 KB)
**Errors:** X
**Warnings:** X
**Output Snippet:**
[First 10 lines of build output]
**Timestamp:** YYYY-MM-DD HH:MM:SS
Template 3: Code Quality Evidence
Use this template for linting and type checking:
## Code Quality Evidence
**Linter:** ESLint / Ruff / etc.
**Command:** `npm run lint`
**Exit Code:** 0 ✅ / non-zero ❌
**Errors:** X
**Warnings:** X
**Type Checker:** TypeScript / mypy / etc.
**Command:** `npm run typecheck`
**Exit Code:** 0 ✅ / non-zero ❌
**Type Errors:** X
**Timestamp:** YYYY-MM-DD HH:MM:SS
Evidence Verification
Quality Standards
Minimum Acceptable
✅ Tests executed with captured exit code ✅ Timestamp recorded ✅ Evidence stored in context
Production-Grade
✅ Tests pass (exit code 0) ✅ Coverage ≥70% (or project standard) ✅ Build succeeds (exit code 0) ✅ No critical linter errors ✅ Type checker passes ✅ Security scan shows no critical issues
Gold Standard
✅ All production-grade requirements ✅ Coverage ≥80% ✅ No linter warnings ✅ Performance benchmarks within thresholds ✅ Accessibility audit passes (WCAG 2.1 AA) ✅ Integration tests pass ✅ Deployment verification complete
Evidence Verification
Common Pitfalls
❌ Don't Skip Evidence Collection
Bad:
"I've implemented the login feature. It should work correctly."
Good:
"I've implemented the login feature. Evidence:
- Tests: Exit code 0, 12 tests passed, 0 failed
- Build: Exit code 0, no errors
- Coverage: 89%
Task complete with verification."
❌ Don't Fake Evidence
Bad:
"Tests passed" (without actually running them)
Good:
"Tests passed. Exit code: 0
Command: npm test
Output: Test Suites: 3 passed, 3 total
Timestamp: 2025-11-02 10:30:15"
❌ Don't Ignore Failed Evidence
Bad:
"Build failed with exit code 1, but the code looks correct so marking complete."
Good:
"Build failed with exit code 1. Errors:
- TypeError: Cannot read property 'id' of undefined (line 42)
Fixing the error now before marking complete."
Evidence Verification
Quick Reference
Evidence Collection Checklist
Before marking task complete:
- [ ] Tests executed
- [ ] Test exit code captured (0 = pass)
- [ ] Build executed (if applicable)
- [ ] Build exit code captured (0 = pass)
- [ ] Code quality checks run (linter, types)
- [ ] Evidence documented with timestamp
- [ ] Evidence added to shared context
- [ ] Evidence summary in completion message
Common Commands by Language/Framework
JavaScript/TypeScript:
npm test # Run tests
npm run build # Build project
npm run lint # Run ESLint
npm run typecheck # Run TypeScript compiler
Python:
pytest # Run tests
pytest --cov # Run tests with coverage
ruff check . # Run linter
mypy . # Run type checker
Evidence Verification
Remember: Evidence-first development prevents hallucinations, ensures production quality, and builds confidence. When in doubt, collect more evidence, not less.
Related Skills
unit-testing- Unit test patterns for generating test evidenceintegration-testing- Integration test patterns for component verificationsecurity-scanning- Security scan evidence collection (npm audit, pip-audit)test-standards-enforcer- Enforce evidence collection standards
Key Decisions
| Decision | Choice | Rationale |
|---|---|---|
| Minimum Coverage | 70% | Industry standard for production-grade code |
| Exit Code Requirement | 0 = pass | Unix standard for success/failure indication |
| Gold Standard Coverage | 80% | Higher bar for critical paths |
| Retry Before Block | 2 attempts | Allow fix attempts before escalation |
Capability Details
exit-code-validation
Keywords: exit code, return code, success, failure, status, $?, exit 0, non-zero Solves:
- How do I verify command succeeded?
- Check exit codes for evidence (0 = pass)
- Validate build/test success with exit codes
- Capture command exit status in evidence
test-evidence
Keywords: test results, test output, coverage report, test evidence, jest, pytest, test suite, passed, failed Solves:
- How do I capture test evidence?
- Record test results in session state
- Prove tests passed with exit code 0
- Document test coverage percentage
- Capture passed/failed/skipped counts
build-evidence
Keywords: build log, build output, compile, bundle, webpack, vite, cargo build, npm build Solves:
- How do I capture build evidence?
- Record build success with exit code
- Verify compilation without errors
- Document build artifacts created
- Track build duration and warnings
code-quality-evidence
Keywords: linter, lint, eslint, ruff, type check, mypy, typescript, code quality, warnings, errors Solves:
- How do I capture code quality evidence?
- Run linter and capture results
- Execute type checker and record errors
- Document linter errors and warnings count
- Prove code quality checks passed
deployment-evidence
Keywords: deployment, deploy, production, staging, health check, rollback, deployment status Solves:
- How do I verify deployment succeeded?
- Check health endpoints after deploy
- Verify application started successfully
- Document deployment status and environment
- Confirm rollback capability exists
security-scan-evidence
Keywords: security, vulnerability, npm audit, pip-audit, security scan, cve, critical vulnerabilities Solves:
- How do I capture security scan results?
- Run npm audit or pip-audit
- Document critical vulnerabilities found
- Record security scan exit code
- Prove no critical security issues
evidence-storage
Keywords: session state, state.json, evidence storage, record evidence, save results, quality_evidence, context 2.0 Solves:
- How do I store evidence in context?
- Update session/state.json with results
- Structure evidence data properly
- Add timestamp to evidence records
- Link to evidence log files
combined-evidence-report
Keywords: evidence report, task completion, verification summary, proof of completion, comprehensive evidence Solves:
- How do I create complete evidence report?
- Combine test, build, and quality evidence
- Create task completion evidence summary
- Document all verification checks run
- Provide comprehensive proof of completion
evidence-collection-workflow
Keywords: evidence workflow, verification steps, evidence protocol, collection process, verification checklist Solves:
- What steps to collect evidence?
- Follow evidence collection protocol
- Run all necessary verification checks
- Complete evidence checklist before marking done
- Ensure minimum evidence requirements met
quality-standards
Keywords: quality standards, minimum requirements, production-grade, gold standard, evidence thresholds Solves:
- What evidence is required to pass?
- Understand minimum vs production-grade standards
- Meet gold standard evidence requirements
- Know when evidence is sufficient
- Validate evidence meets project standards
evidence-pitfalls
Keywords: evidence mistakes, common errors, skip evidence, fake evidence, ignore failures Solves:
- What evidence mistakes to avoid?
- Never skip evidence collection
- Don't fake evidence results
- Don't ignore failed evidence
- Always re-collect after changes
Score
Total Score
Based on repository quality metrics
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