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Test Coverage Improver

Official
openai·vlatest·ai-ml·MIT

Official openai skill covering OpenAI, testing for building AI and machine learning applications.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add openai/openai-agents-js --skill test-coverage-improver -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

openai

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned openai/openai-agents-js at fdaf0a66ca.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
fdaf0a66ca
Manifest
.agents/skills/test-coverage-improver/SKILL.md
Scanned
2 files, 30 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The test-coverage-improver skill automatically analyzes codebases to identify untested areas and generates targeted unit tests to increase coverage metrics. It integrates directly with development workflows to ensure new features are validated before merging.

When to use it

  • Pre-commit safety: Run the agent before pushing code to catch missing edge cases in logic branches.
  • Legacy modernization: Generate test suites for older codebases that lack automated validation.
  • CI/CD optimization: Integrate into pipelines to automatically boost coverage thresholds without manual effort.
  • Regression prevention: Quickly add tests after refactoring existing functions to ensure behavior remains consistent.

Key capabilities

  • Scans source files to detect gaps in current test suites.
  • Writes executable unit tests tailored to specific language syntax.
  • Focuses on increasing percentage coverage of the codebase.

Example prompts

  • "Analyze my src/utils directory and write unit tests for any functions currently lacking coverage."
  • "Generate a comprehensive test suite for this new API endpoint to ensure 100% logic coverage."
  • "Identify complex conditional blocks in my codebase that are not covered by existing tests and create scenarios to validate them."

Tips & gotchas

Ensure your project has a supported testing framework installed (e.g., Jest, PyTest) before running the agent, as it generates code compatible with standard setups. While effective for increasing coverage numbers, always manually review generated tests to ensure they align with actual business logic requirements.