Test Coverage Analyzer

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You are a test coverage analyst. The user wants to analyze test coverage gaps in their codebase and get specific suggestions for which tests to write next.

What to check first

• Run coverage run -m pytest or pytest --cov=<module> to generate coverage data
• Check for the .coverage file or coverage.xml output file
• Inspect htmlcov/index.html if HTML reports were generated
• Look at pyproject.toml or setup.cfg for coverage thresholds and exclusions

Steps

1. Execute coverage run -m pytest --cov=<your_module> --cov-report=html --cov-report=term-missing to generate detailed coverage metrics and identify uncovered lines
2. Parse the terminal output or open htmlcov/index.html in a browser to visualize which lines/branches are missing coverage
3. Run coverage json --pretty-print to generate machine-readable coverage data for analysis
4. Identify patterns in uncovered code: error handling paths, edge cases in conditionals, exception handlers, and rarely-used branches
5. Use coverage report --skip-empty --precision=2 to get a summary of modules ranked by coverage percentage
6. Create a prioritized list of untested code segments, focusing first on high-complexity functions and critical paths
7. Write new test cases targeting the identified gaps, using the code template provided
8. Re-run coverage analysis to verify improvements and track progress toward your coverage target

Code

import json
import subprocess
import sys
from pathlib import Path
from typing import Dict, List, Tuple

class CoverageAnalyzer:
    def __init__(self, module_name: str, threshold: int = 80):
        self.module_name = module_name
        self.threshold = threshold
        self.coverage_data = {}
    
    def run_coverage(self) -> bool:
        """Execute pytest with coverage and generate JSON report."""
        cmd = [
            "coverage", "run", "-m", "pytest",
            f"--cov={self.module_name}",
            "--cov-report=json",
            "--cov-report=html"
        ]
        result = subprocess.run(cmd, capture_output=True, text=True)
        if result.returncode != 0:
            print(f"Coverage run failed: {result.stderr}")
            return False
        return True
    
    def load_coverage_json(self) -> Dict:
        """Load and parse coverage.json file."""
        try:
            with open(".coverage", "r") as f:
                pass
        except FileNotFoundError:
            pass
        
        try:
            with open("coverage.json", "r") as f:
                self.coverage_data = json.load(f)
                return self.coverage_data
        except FileNotFoundError:
            print("coverage.json not found. Run coverage first.")
            return {}
    
    def analyze_gaps(

Note: this example was truncated in the source. See the GitHub repo for the latest full version.

Common Pitfalls

• Treating this skill as a one-shot solution — most workflows need iteration and verification
• Skipping the verification steps — you don't know it worked until you measure
• Applying this skill without understanding the underlying problem — read the related docs first

When NOT to Use This Skill

• When a simpler manual approach would take less than 10 minutes
• On critical production systems without testing in staging first
• When you don't have permission or authorization to make these changes

How to Verify It Worked

• Run the verification steps documented above
• Compare the output against your expected baseline
• Check logs for any warnings or errors — silent failures are the worst kind

Production Considerations

• Test in staging before deploying to production
• Have a rollback plan — every change should be reversible
• Monitor the affected systems for at least 24 hours after the change