test-coverage-improver

Run make coverage, analyze reports, and propose high-impact tests for approval.

Updated Jan 17, 2026
One-click install
npx skills add https://github.com/zaziedlm/openai-agents-python --skill test-coverage-improver
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: test-coverage-improver
Source: https://github.com/zaziedlm/openai-agents-python/tree/main/.codex/skills/test-coverage-improver
Command: npx skills add https://github.com/zaziedlm/openai-agents-python --skill test-coverage-improver

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the need to improve and maintain high test coverage within the OpenAI Agents Python repository, ensuring code robustness and reliability.

Core Features & Use Cases

  • Coverage Analysis: Runs make coverage to generate coverage reports (.coverage, coverage.xml).
  • Gap Identification: Analyzes coverage reports to pinpoint files and lines with low or no test coverage.
  • Test Proposal: Suggests high-impact tests to cover identified gaps, prioritizing critical code areas.
  • User Confirmation: Seeks explicit user approval before implementing any new tests.
  • Test Implementation: Writes new tests in the tests/ directory after approval.
  • Verification: Reruns coverage and uses $code-change-verification to confirm improvements.

Quick Start

Run make coverage from the repo root to regenerate coverage data and then analyze the results.

Frequently Asked Questions about test-coverage-improver

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I improve test coverage in my Python repository?

To improve test coverage, run `make coverage` to generate reports, analyze the artifacts to pinpoint low-coverage files, and propose high-impact tests to systematically address gaps in your suite.

How does analyzing coverage artifacts identify untested code?

Analyzing coverage artifacts identifies untested code by parsing `.coverage` and `coverage.xml` reports to map executed lines, pinpointing specific files and lines with low or no test coverage.

What is the process for proposing new tests after running coverage analysis?

The process for proposing new tests involves analyzing coverage reports to identify gaps, suggesting high-impact tests that prioritize critical code areas, and seeking explicit user approval before implementing them.

Can I use this approach to verify code quality improvements after refactoring?

Yes, you can verify code quality improvements by rerunning coverage analysis and using code-change-verification to confirm that newly implemented tests successfully address identified coverage gaps.

Does generating test coverage reports require specific tools or environments?

Generating test coverage reports requires executing the `make coverage` command from the repository root to produce the necessary `.coverage` and `coverage.xml` artifacts for gap analysis.

What are the limitations of automated test gap identification?

A limitation of automated test gap identification is that it requires existing coverage artifacts to analyze, meaning you must execute coverage tools successfully first and approve proposed tests before implementation.