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Fix software bugs with a disciplined reproduce-first workflow. Before touching any code, understand the root cause and capture the bug in a regression test. Then apply the minimal fix, verify all tests pass, and finish with linting and quality checks. The regression test stays in the codebase to prevent re-introduction.

• $ARGUMENTS: required — one of:
  • A bug description in plain text (e.g., "TypeError when passing None to transform()")
  • A GitHub issue number (e.g., 123 — fetched via gh issue view)
  • An error message or traceback snippet
  • A failing test name (e.g., tests/test_transforms.py::test_none_input)

Task tracking: per CLAUDE.md, create tasks (TaskCreate) for each major phase. Mark in_progress/completed throughout. On loop retry or scope change, create a new task.

Step 1: Understand the problem

Gather all available context about the bug:

bash
1# If issue number: fetch the full issue with comments
2gh issue view <number> --comments

If an error message or pattern was provided: use the Grep tool (pattern <error_pattern>, path .) to search the codebase for the failing code path. Adjust to src/, lib/, or app/ as appropriate for the project layout.

bash
1
2# If failing test: run it to capture the exact failure
3python -m pytest <test_path> -v --tb=long 2>&1 | tail -40

Spawn a sw-engineer agent to analyze the failing code path and identify:

• The root cause (not just the symptom)
• The minimal code surface that needs to change
• Any related code that might be affected by the fix

Step 2: Reproduce the bug

Create or identify a test that demonstrates the failure:

bash
1# If a failing test already exists — run it to confirm it fails
2python -m pytest <test_file>::<test_name> -v --tb=short
3
4# If no test exists — write a regression test that captures the bug
5# Name it: test_<function>_<bug_description> (e.g., test_transform_none_input)

Spawn a qa-specialist agent to write the regression test if one doesn't exist:

• The test must fail against the current code (proving the bug exists)
• Use pytest.mark.parametrize if the bug affects multiple input patterns
• Keep the test minimal — exercise exactly the broken behavior
• Add a brief comment linking to the issue if applicable (e.g., # Regression test for #123)

Gate: the regression test must fail before proceeding. If it passes, the bug isn't properly captured — revisit Step 1.

Step 3: Apply the fix

Make the minimal change to fix the root cause:

1. Edit only the code necessary to resolve the bug
2. Run the regression test to confirm it now passes:

   bash
   1python -m pytest <test_file>::<test_name> -v --tb=short

3. Run the full test suite for the affected module to check for regressions:

   bash
   1# Step 3: regression gate — confirms fix does not break existing tests
   2python -m pytest <test_dir> -v --tb=short

4. If any existing tests break: the fix has side effects — reconsider the approach

Step 4: Linting and quality

Spawn a linting-expert agent (or run directly) to ensure the fix meets code quality standards:

bash
1# Run ruff for linting and formatting
2ruff check <changed_files> --fix
3ruff format <changed_files>
4
5# Run mypy for type checking if configured
6mypy <changed_files> --no-error-summary 2>&1 | head -20
7
8# Step 4: final full-suite clean run before commit
9python -m pytest <test_dir> -v --tb=short

Step 5: Verify and report

Output a structured report:

## Fix Report: <bug summary>

### Root Cause
[1-2 sentence explanation of what was wrong and why]

### Regression Test
- File: <test_file>
- Test: <test_name>
- Confirms: [what behavior the test locks in]

### Changes Made
| File | Change | Lines |
|------|--------|-------|
| path/to/file.py | description of fix | -N/+M |

### Test Results
- Regression test: PASS
- Full suite: PASS (N tests)
- Lint: clean

### Follow-up
- [any related issues or code that should be reviewed]

## Confidence
**Score**: [0.N]
**Gaps**: [e.g., could not reproduce locally, partial traceback only, fix not runtime-tested]

Team Mode (--team)

Use when the bug has competing root-cause hypotheses or spans multiple modules. Skip for single-file bugs — use the default workflow above.

When to trigger: root cause is unclear after Step 1, OR the bug manifests across 3+ modules.

Workflow with --team:

1. Lead spawns 2–3 sw-engineer teammates, each investigating a distinct hypothesis
2. Broadcast current evidence to all teammates: broadcast {bug: <description>, traceback: <key lines>}
3. Each teammate investigates independently — announces with alpha PROTO:v2.0 and claims a hypothesis
4. Teammates report findings via lead (hub-and-spoke); lead facilitates cross-challenge between competing analyses
5. Lead synthesizes the consensus root cause, then proceeds with Steps 2–5 above (regression test, fix, lint, report) — all in lead context

Spawn prompt template:

You are a sw-engineer teammate debugging: [bug description].
Read .claude/TEAM_PROTOCOL.md — use AgentSpeak v2 for inter-agent messages.
Your hypothesis: [hypothesis N]. Investigate ONLY this root cause.
Report findings to @lead using deltaT# or epsilonT# codes.
Compact Instructions: preserve file paths, errors, line numbers. Discard verbose tool output.

• Reproduce first: never fix a bug you can't demonstrate with a test — the test is the proof
• Minimal fix: change only what's necessary to resolve the root cause — avoid incidental refactoring
• The regression test is a permanent contribution — it prevents the bug from recurring
• If the bug is in .claude/ config files: run self-mentor audit + /sync after fixing
• Related agents: sw-engineer (root cause analysis), qa-specialist (regression test), linting-expert (quality)
• Follow-up chains:
  • Fix involves structural improvements beyond the bug → /refactor for test-first code quality pass
  • Fix touches non-trivial code paths → /review for full multi-agent quality validation
  • Fix required consistent renames or annotation changes across many files → /codex to delegate the mechanical sweep