The 'test-fixing' skill is a systematic automation tool designed to identify, categorize, and resolve software test failures. By utilizing smart error grouping based on error types, modules, and root causes, it streamlines the debugging process, allowing developers to efficiently restore test suites to a passing state after refactoring, dependency updates, or CI/CD failures.

When should I use test-fixing?

test-fixing is useful in the following scenarios: • 1. Post-Refactoring Stabilization: Automatically fix widespread test failures resulting from renamed modules or changed function signatures after significant code changes. • 2. CI/CD Failure Resolution: Rapidly address broken builds by systematically triaging and fixing errors reported in continuous integration pipelines. • 3. Dependency Upgrade Support: Efficiently resolve import errors and configuration issues that occur when updating project dependencies or frameworks. • 4. Regression Debugging: Identify and fix logic bugs introduced during new feature development to ensure the entire codebase remains stable.

name	test-fixing
description	Run tests and systematically fix all failing tests using smart error grouping. Use when user asks to fix failing tests, mentions test failures, runs test suite and failures occur, or requests to make tests pass.

Test Fixing

Systematically identify and fix all failing tests using smart grouping strategies.

When to Use

Explicitly asks to fix tests ("fix these tests", "make tests pass")
Reports test failures ("tests are failing", "test suite is broken")
Completes implementation and wants tests passing
Mentions CI/CD failures due to tests

Systematic Approach

1. Initial Test Run

Run make test to identify all failing tests.

Analyze output for:

Total number of failures
Error types and patterns
Affected modules/files

2. Smart Error Grouping

Group similar failures by:

Error type: ImportError, AttributeError, AssertionError, etc.
Module/file: Same file causing multiple test failures
Root cause: Missing dependencies, API changes, refactoring impacts

Prioritize groups by:

Number of affected tests (highest impact first)
Dependency order (fix infrastructure before functionality)

3. Systematic Fixing Process

For each group (starting with highest impact):

Identify root cause
- Read relevant code
- Check recent changes with git diff
- Understand the error pattern
Implement fix
- Use Edit tool for code changes
- Follow project conventions (see CLAUDE.md)
- Make minimal, focused changes
Verify fix
- Run subset of tests for this group
- Use pytest markers or file patterns:
```
uv run pytest tests/path/to/test_file.py -v
uv run pytest -k "pattern" -v
```
- Ensure group passes before moving on
Move to next group

4. Fix Order Strategy

Infrastructure first:

Import errors
Missing dependencies
Configuration issues

Then API changes:

Function signature changes
Module reorganization
Renamed variables/functions

Finally, logic issues:

Assertion failures
Business logic bugs
Edge case handling

5. Final Verification

After all groups fixed:

Run complete test suite: make test
Verify no regressions
Check test coverage remains intact

Best Practices

Fix one group at a time
Run focused tests after each fix
Use git diff to understand recent changes
Look for patterns in failures
Don't move to next group until current passes
Keep changes minimal and focused

Example Workflow

User: "The tests are failing after my refactor"

Run make test → 15 failures identified
Group errors:
- 8 ImportErrors (module renamed)
- 5 AttributeErrors (function signature changed)
- 2 AssertionErrors (logic bugs)
Fix ImportErrors first → Run subset → Verify
Fix AttributeErrors → Run subset → Verify
Fix AssertionErrors → Run subset → Verify
Run full suite → All pass ✓

test-fixing

When & Why to Use This Skill

Use Cases