How does this skill group test errors?

The skill analyzes test output to group failures by error type (e.g., ImportError, AttributeError), the specific module or file affected, and shared root causes like missing dependencies.

Can I use this with pytest?

Yes, the skill is designed to work with standard test runners like pytest and can execute focused test subsets using markers or file patterns for faster iteration.

Does the skill verify its own fixes?

Absolutely. The skill follows a systematic process of implementing a fix, running the relevant subset of tests to verify it, and finally running the entire suite to ensure no regressions.

Why does it prioritize infrastructure fixes first?

Fixing infrastructure issues like imports and configurations first often resolves dozens of downstream test failures at once, making it the most efficient way to clear a broken suite.

Test Failure Resolver

Name: Test Failure Resolver
Author: hueyjeong

byhueyjeong

Security & Testing

Systematically identifies and repairs failing tests using intelligent error grouping and prioritized fixing strategies.

About

The Test Failure Resolver skill empowers Claude to efficiently manage and fix broken test suites by moving beyond a trial-and-error approach. It analyzes test outputs to group related failures—such as ImportErrors, API signature changes, or logic bugs—and prioritizes them logically to resolve infrastructure issues before fine-tuning business logic. This skill is essential for developers dealing with regression cycles, major refactors, or CI/CD failures, ensuring a stable codebase through automated verification and methodical debugging.

Key Features

Focused test execution for rapid verification of specific fixes
Full suite regression testing to ensure comprehensive stability
0 GitHub stars
Prioritized fixing strategy starting with infrastructure and dependencies
Smart error grouping by type, module, and root cause
Automatic pattern recognition across multiple failing test cases

Use Cases

Updating test assertions and mocks to match recent API signature updates
Resolving systemic CI/CD pipeline failures due to environment or dependency changes
Repairing a test suite after a large-scale codebase refactor

About

Key Features

Focused test execution for rapid verification of specific fixes
Full suite regression testing to ensure comprehensive stability
0 GitHub stars
Prioritized fixing strategy starting with infrastructure and dependencies
Smart error grouping by type, module, and root cause
Automatic pattern recognition across multiple failing test cases

Use Cases

Updating test assertions and mocks to match recent API signature updates
Resolving systemic CI/CD pipeline failures due to environment or dependency changes
Repairing a test suite after a large-scale codebase refactor