coverage-reporter

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

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:

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