---

name: coverage-reporter description: Generate and analyze test coverage reports. Use to identify coverage gaps, track coverage trends, and ensure quality thresholds are met. model_tier: sonnet parallel_hints: can_parallel_with: [test-writer, code-review, lint-monorepo] must_serialize_with: [] preferred_batch_size: 5 context_hints: max_file_context: 100 compression_level: 2 requires_git_context: true requires_db_context: false escalation_triggers:

• pattern: "coverage.*below.*threshold" reason: "Coverage below minimum requires human decision"
• keyword: ["critical", "untested"] reason: "Untested critical code needs attention"

---

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

Copycd backend
pytest --cov=app --cov-report=html --cov-report=term-missing

TypeScript Coverage

Copycd frontend
npm run test:coverage

Phase 2: Gap Analysis

Step 2.1: Identify Untested Code

CopyFor 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

Phase 3: Coverage Report Generation

Copy## 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

Copy1. 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

Quick Coverage Commands

Copy# 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:

Copy1. 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:

1. Report findings to test-writer skill
2. Request test generation for gaps
3. Re-run coverage after tests added
4. 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