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coverage-reporter

maintained by Euda1mon1a

star 2 account_tree 0 verified_user MIT License
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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

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Skill Details

GitHub Stars 2
GitHub Forks 0
Created Jan 2026
Last Updated 5 months ago
tools tools automation tools

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