Can it identify specific uncovered lines of code?

Yes, it parses coverage.xml and console reports to pinpoint the exact lines and logical paths that lack unit or integration tests.

Which testing tools does this skill work with?

It is optimized for Python environments using standard coverage tools, specifically those triggered via make coverage or coverage.py commands.

Can it help with async and concurrency testing?

Yes, it is designed to analyze risky code paths including concurrency and async logic, proposing robust tests that avoid common pitfalls like flaky timing.

Does this skill automatically modify my code?

No, the skill identifies gaps and proposes specific test scenarios, requiring explicit user approval before any test files are written or modified.

How does it prioritize which tests to write first?

The skill prioritizes public APIs, shared utilities, and high-risk logic like error handling, retries, and timeouts over trivial happy paths.

Test Coverage Improver

Name: Test Coverage Improver
Author: zaziedlm

byzaziedlm

Security & Testing

Automates the identification of code coverage gaps and generates high-impact tests to strengthen software reliability.

About

The Test Coverage Improver is a specialized Claude Code skill designed to streamline the quality assurance process by automatically managing the testing lifecycle. It executes coverage suites, parses complex artifacts like coverage.xml, and pinpoints specific lines or logic paths that lack adequate testing. By prioritizing high-risk areas such as public APIs, error handling, and concurrency logic, the skill provides structured test proposals for user approval. This ensures that developers can maintain high testing standards and prevent coverage regressions with minimal manual effort, specifically tailored for Python-based agentic workflows.

Key Features

Identification of low-coverage files and mission-critical code gaps
Automated coverage suite execution and report analysis
Design of targeted test cases for error paths and boundary conditions
Interactive proposal workflow for user-approved test implementation
Post-implementation verification and coverage delta reporting
0 GitHub stars

Use Cases

Ensuring new features or bug fixes meet strict project testing thresholds
Hardening mission-critical agent logic against failures and timeouts
Closing coverage gaps in complex Python repositories and shared utilities

About

Key Features

Identification of low-coverage files and mission-critical code gaps
Automated coverage suite execution and report analysis
Design of targeted test cases for error paths and boundary conditions
Interactive proposal workflow for user-approved test implementation
Post-implementation verification and coverage delta reporting
0 GitHub stars

Use Cases

Ensuring new features or bug fixes meet strict project testing thresholds
Hardening mission-critical agent logic against failures and timeouts
Closing coverage gaps in complex Python repositories and shared utilities