coverage-boost

What This Skill Does

Coverage Boost is a specialized OpenClaw agent skill designed to bridge the gap between current test coverage and your team's quality targets. By analyzing your existing source code and coverage reports, it programmatically identifies logic branches, edge cases, and boundary conditions that have been neglected. Instead of manually writing boilerplate for uncovered paths, this tool generates high-quality unit tests that integrate directly into your existing testing ecosystem. Whether you are struggling to reach a specific metric like 80% coverage or simply want to improve the robustness of your codebase, this agent automates the tedious task of gap analysis and code generation.

Installation

To install this skill, ensure your environment meets the Node.js 18+ requirement and you have an active OPENAI_API_KEY. Run the following command in your terminal within your OpenClaw-enabled project:

clawhub install openclaw/skills/skills/lxgicstudios/ai-coverage-boost

Ensure that you have an existing coverage report (e.g., coverage/lcov.info) generated by your test runner, as the tool uses this data to map out missing segments more accurately.

Use Cases

• Increasing Test Coverage: Automatically generate tests to meet specific organizational benchmarks.
• Refactoring Confidence: Generate tests for legacy modules before modifying them to ensure safety.
• Boundary Analysis: Identify potential crashes by forcing the agent to create inputs for extreme input parameters.
• CI/CD Optimization: Add a step in your pipeline to generate missing tests dynamically before deployments.

Example Prompts

1. "OpenClaw, use coverage-boost on ./src/services/auth.ts and generate unit tests for all missing branches using the Jest framework."
2. "I need to boost our test coverage; run coverage-boost on the entire ./src directory and prioritize the login function."
3. "Analyze the current coverage report for the project and generate tests for the uncovered error-handling blocks in our payment processing module."

Tips & Limitations

• Tip: Always review the generated code. While the agent is highly accurate, generated tests should be integrated into your suite only after a peer review.
• Tip: Run your test suite immediately after generation to ensure the new tests pass.
• Limitation: The tool relies on your existing coverage reports. If the reports are outdated, the agent may target incorrect paths.
• Limitation: Large files might require splitting into smaller chunks for the AI to provide the most contextually relevant test cases.