Test Fixing

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 failure
• 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):

1. Identify root cause

   • Read relevant code
   • Check recent changes with git diff
   • Understand the error pattern

2. Implement fix

   • Use Edit tool for code changes
   • Follow project conventions (see CLAUDE.md)
   • Make minimal, focused changes

3. 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

4. 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"

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

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior test strategies, known flaky tests, and coverage gaps. Cache test infrastructure setup to avoid re-configuring test environments.

# Check for prior testing/QA context before starting
python3 execution/memory_manager.py auto --query "test patterns and coverage strategies for Test Fixing"

Storing Results

After completing work, store testing/QA decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Testing strategy: integration tests hit real DB (no mocks), 85% line coverage, mutation testing on critical paths" \
  --type technical --project <project> \
  --tags test-fixing testing

Multi-Agent Collaboration

Share test results and coverage reports with code review agents so they can verify adequate coverage on changed code.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "QA complete — test suite expanded with 12 new integration tests, all passing" \
  --project <project>

TDD Enforcement

This skill integrates with the framework's iron-law RED-GREEN-REFACTOR cycle. No production code without a failing test first.

Agent Team: QA

Dispatch qa_team to generate tests and verify they pass before marking implementation complete.