Claude-skill-registry coverage-reporter
Generate and analyze test coverage reports. Use to identify coverage gaps, track coverage trends, and ensure quality thresholds are met.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/coverage-reporter" ~/.claude/skills/majiayu000-claude-skill-registry-coverage-reporter && rm -rf "$T"
manifest:
skills/data/coverage-reporter/SKILL.mdsource content
Coverage Reporter Skill
Comprehensive test coverage analysis and reporting for Python and TypeScript code.
When This Skill Activates
- After running test suite
- Before committing changes
- Tracking coverage over time
- Investigating coverage gaps
- Reporting on coverage metrics
Coverage Analysis Methodology
Phase 1: Coverage Collection
Python Coverage
cd backend pytest --cov=app --cov-report=html --cov-report=term-missing
TypeScript Coverage
cd frontend npm run test:coverage
Phase 2: Gap Analysis
Step 2.1: Identify Untested Code
For each file: 1. Count lines not covered 2. Identify untested functions 3. Identify untested branches 4. Calculate coverage percentage
Step 2.2: Prioritize by Risk
| Risk Level | Type | Priority |
|---|---|---|
| Critical | Auth, crypto, data access | Fix immediately |
| High | Business logic, validation | Fix within 48h |
| Medium | Utils, helpers | Fix within 1 week |
| Low | Formatting, display | Nice to have |
Phase 3: Coverage Report Generation
## Test Coverage Report **Date:** [DATE] **Overall Coverage:** [X]% ### Summary - Backend: [X]% - Frontend: [Y]% - Target: 80% ### Critical Gaps - [File]: [X]% - [reason] - [File]: [Y]% - [reason] ### Trends - Week 1: 75% - Week 2: 77% - Week 3: 79% - Trend: Improving ### Recommendations 1. [Recommendation 1] 2. [Recommendation 2]
Phase 4: Trend Analysis
1. Historical coverage - Track weekly/monthly trends - Identify degradation - Project future coverage 2. Coverage velocity - How fast is coverage improving? - Estimate time to target 3. Coverage stability - Which areas consistently low? - Which areas consistently high?
Coverage Requirements by Layer
| Layer | Target | Minimum |
|---|---|---|
| Services | 90% | 80% |
| Controllers | 85% | 75% |
| Models | 80% | 70% |
| Utils | 90% | 85% |
| Routes | 75% | 65% |
| Components (Frontend) | 80% | 70% |
Quick Coverage Commands
# Python coverage with details cd backend pytest --cov=app --cov-report=html --cov-report=term-missing -v # Frontend coverage cd frontend npm run test:coverage # Coverage diff against main # (Identify what new code is untested) git diff main...HEAD | grep "^+" | wc -l
Gap Remediation Workflow
For Each Untested Component:
1. Understand the code - What does it do? - When is it called? - Why isn't it tested? 2. Determine test strategy - Unit test? - Integration test? - E2E test? 3. Write tests - Happy path - Error cases - Edge cases 4. Verify coverage - Re-run coverage - Confirm improved
Integration with test-writer
When coverage gaps identified:
- Report findings to test-writer skill
- Request test generation for gaps
- Re-run coverage after tests added
- Track improvement
Validation Checklist
- Coverage >= target percentage
- No untested critical code
- All public APIs covered
- Error paths tested
- Edge cases covered
- Coverage trend is improving
- No artificial coverage inflation
References
- Coverage requirements in CLAUDE.md
- See test-writer skill for test generation
- Testing patterns in python-testing-patterns skill