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coverage-reporter

majiayu000
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Metatesting

About

The coverage-reporter skill generates and analyzes test coverage reports for Python and TypeScript to identify gaps and track trends. It activates after test runs or before commits to ensure quality thresholds are met. The skill requires git context and can parallelize with testing and code review workflows.

Quick Install

Claude Code

Recommended
Plugin CommandRecommended
/plugin add https://github.com/majiayu000/claude-skill-registry
Git CloneAlternative
git clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/coverage-reporter

Copy and paste this command in Claude Code to install this skill

Documentation

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 LevelTypePriority
CriticalAuth, crypto, data accessFix immediately
HighBusiness logic, validationFix within 48h
MediumUtils, helpersFix within 1 week
LowFormatting, displayNice 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

LayerTargetMinimum
Services90%80%
Controllers85%75%
Models80%70%
Utils90%85%
Routes75%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

GitHub Repository

majiayu000/claude-skill-registry
Path: skills/coverage-reporter

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