Agent-alchemy bug-killer

install
source · Clone the upstream repo
git clone https://github.com/sequenzia/agent-alchemy
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sequenzia/agent-alchemy "$T" && mkdir -p ~/.claude/skills && cp -r "$T/claude/dev-tools/skills/bug-killer" ~/.claude/skills/sequenzia-agent-alchemy-bug-killer && rm -rf "$T"
manifest: claude/dev-tools/skills/bug-killer/SKILL.md
source content

Bug Killer — Hypothesis-Driven Debugging Workflow

Execute a systematic debugging workflow that enforces investigation before fixes. Every bug gets a hypothesis journal, evidence gathering, and root cause confirmation before any code changes.

CRITICAL: Complete ALL 5 phases. The workflow is not complete until Phase 5: Wrap-up & Report is finished. After completing each phase, immediately proceed to the next phase without waiting for user prompts.

Phase Overview

  1. Triage & Reproduction — Understand, reproduce, route to quick or deep track
  2. Investigation — Gather evidence with language-specific techniques
  3. Root Cause Analysis — Confirm root cause through hypothesis testing
  4. Fix & Verify — Fix with proof, regression test, quality check
  5. Wrap-up & Report — Document trail, capture learnings

Phase 1: Triage & Reproduction

Goal: Understand the bug, reproduce it, and decide the investigation track.

1.1 Parse Context

Extract from

$ARGUMENTS
and conversation context:

  • Bug description: What's failing? Error messages, symptoms
  • Reproduction steps: How to trigger the bug (test command, user action, etc.)
  • Environment: Language, framework, test runner, relevant config
  • Prior attempts: Has the user already tried fixes? What didn't work?
  • Deep flag: If
    --deep
    is present, skip triage and go directly to deep track (jump to Phase 2 deep track)

1.2 Reproduce the Bug

Attempt to reproduce before investigating:

  1. If a failing test was mentioned, run it:
    # Run the specific test to confirm the failure
    <test-runner> <test-file>::<test-name>
    
  2. If an error was described, find and trigger it
  3. If neither, search for related test files and run them

Capture the exact error output — this is your primary evidence.

If the bug cannot be reproduced:

  • Ask the user for more context via AskUserQuestion
  • Check if it's environment-specific or intermittent
  • Note "not yet reproduced" in the hypothesis journal

1.3 Form Initial Hypothesis

Based on the error message and context, form your first hypothesis:

### H1: [Title]
- Hypothesis: [What you think is causing the bug]
- Evidence for: [What supports this — error message, stack trace, etc.]
- Evidence against: [Anything that contradicts it — if none yet, say "None yet"]
- Test plan: [Specific steps to confirm or reject]
- Status: Pending

1.4 Route to Track

Quick-fix signals (ALL must be true):

  • Clear, specific error message pointing to exact location
  • Localized to 1-2 files (not spread across the codebase)
  • Obvious fix visible from reading the error location
  • No concurrency, timing, or state management involved

Deep-track signals (ANY one triggers deep track):

  • Bug spans 3+ files or modules
  • Root cause unclear from the error message alone
  • Intermittent or environment-dependent failure
  • Involves concurrency, timing, shared state, or async behavior
  • User already tried fixes that didn't work
  • Generic error message (e.g., "null reference" without clear origin)
  • Stack trace points to library/framework code rather than application code

Present your assessment via AskUserQuestion:

  • Summarize the bug and your initial hypothesis
  • Recommend quick or deep track with justification
  • Options: "Quick track (Recommended)" / "Deep track" / "Deep track" / "Quick track" — depending on your assessment
  • Let the user override your recommendation

Track escalation rule: If during quick track execution, 2 hypotheses are rejected, automatically escalate to deep track. Preserve all hypothesis journal entries when escalating.


Phase 2: Investigation

Goal: Gather evidence systematically, guided by language-specific techniques.

2.1 Load Language Reference

Detect the primary language of the bug's context and load the appropriate reference:

LanguageReference File
Python
Read ${CLAUDE_PLUGIN_ROOT}/skills/bug-killer/references/python-debugging.md
TypeScript / JavaScript
Read ${CLAUDE_PLUGIN_ROOT}/skills/bug-killer/references/typescript-debugging.md
Other / Multiple
Read ${CLAUDE_PLUGIN_ROOT}/skills/bug-killer/references/general-debugging.md

Always also load

general-debugging.md
as a supplement when using a language-specific reference.

2.2 Quick Track Investigation

For quick-track bugs, investigate directly:

  1. Read the error location — the file and function where the error occurs
  2. Read the immediate callers — 1-2 files up the call chain
  3. Check recent changes
    git log --oneline -5 -- <file>
    for the affected files
  4. Update hypothesis — does the evidence support H1? Add evidence for/against

Proceed to Phase 3 (quick track).

2.3 Deep Track Investigation

For deep-track bugs, use parallel exploration agents:

  1. Plan exploration areas — identify 2-3 focus areas based on the bug:

    • Focus 1: The error site and immediate code path
    • Focus 2: Data flow and state management leading to the error
    • Focus 3: Related subsystems, configuration, or external dependencies
  2. Launch code-explorer agents:

    Spawn 2-3 code-explorer agents from core-tools:

    Use Task tool with subagent_type: "agent-alchemy-core-tools:code-explorer"
    
    Prompt for each agent:
    Bug context: [description of the bug and error]
    Focus area: [specific area for this agent]
    
    Investigate this focus area in relation to the bug:
    - Find all relevant files
    - Trace the execution/data path
    - Identify where behavior diverges from expected
    - Note any suspicious patterns, recent changes, or known issues
    - Report structured findings
    

    Launch agents in parallel for independent focus areas.

  3. Synthesize exploration results:

    • Collect findings from all agents
    • Identify convergence (multiple agents pointing to same area)
    • Update hypothesis journal with new evidence
    • Form additional hypotheses if evidence warrants (aim for 2-3 total)

Proceed to Phase 3 (deep track).


Phase 3: Root Cause Analysis

Goal: Confirm the root cause through systematic hypothesis testing.

3.1 Quick Track Root Cause

For quick-track bugs:

  1. Verify the hypothesis:

    • Read the specific code identified in Phase 2
    • Trace the logic step-by-step
    • Confirm that the hypothesized cause produces the observed error
  2. If confirmed (Status → Confirmed):

    • Update H1 with confirming evidence
    • Proceed to Phase 4
  3. If rejected (Status → Rejected):

    • Update H1 with evidence against and reason for rejection
    • Form a new hypothesis (H2) based on what you learned
    • Investigate H2 following Phase 2 quick track steps
    • If H2 is also rejected → escalate to deep track
    • Preserve all journal entries, continue with Phase 2 deep track

3.2 Deep Track Root Cause

For deep-track bugs:

  1. Prepare hypotheses for testing:

    • You should have 2-3 hypotheses from Phase 2
    • Each needs a concrete test plan (how to confirm or reject)
  2. Launch bug-investigator agents:

    Spawn 1-3 bug-investigator agents to test hypotheses in parallel:

    Use Task tool with subagent_type: "bug-investigator"
    
    Prompt for each agent:
    Bug context: [description of the bug and error]
    
    Hypothesis to test: [specific hypothesis]
    Test plan:
    1. [Step 1 — e.g., run this specific test with these arguments]
    2. [Step 2 — e.g., check git blame for this function]
    3. [Step 3 — e.g., trace the data from input to error site]
    
    Report your findings with verdict (confirmed/rejected/inconclusive),
    evidence, and recommendations.
    

    Launch agents in parallel when they test independent hypotheses.

  3. Evaluate results:

    • Update hypothesis journal with each agent's findings

    • If one hypothesis is confirmed → proceed to Phase 4

    • If all are rejected/inconclusive → apply 5 Whys technique:

      Take the strongest "inconclusive" finding and ask "why?" iteratively:

      Observed: [what actually happens]
      Why? → [first-level cause]
      Why? → [second-level cause]
      Why? → [root cause]
      
    • Form new hypotheses from 5 Whys analysis and repeat investigation

  4. If stuck after 2 rounds of investigation:

    • Present all findings to the user via AskUserQuestion
    • Share the hypothesis journal
    • Ask for additional context or direction
    • Options: "Continue investigating", "Try a different angle", "Provide more context"

Phase 4: Fix & Verify

Goal: Fix the root cause and prove the fix works.

4.1 Design the Fix

Before writing any code:

  1. Explain the root cause — state clearly what's wrong and why
  2. Explain the fix — describe what will change and WHY it addresses the root cause
  3. Identify affected files — list every file that needs modification
  4. Consider side effects — could this fix break other behavior?

4.2 Implement the Fix

  1. Read all files that will be modified before making changes
  2. Apply the fix using Edit tool — minimal, focused changes
  3. Match existing patterns — follow the codebase's conventions

4.3 Run Tests

  1. Run the originally failing test — it should now pass:

    <test-runner> <test-file>::<test-name>
    
  2. Run related tests — tests in the same file and nearby test files:

    <test-runner> <test-directory>
    
  3. If tests fail:

    • Determine if the failure is related to the fix or pre-existing
    • If related, revise the fix (do NOT revert to a different approach without updating the hypothesis journal)
    • If pre-existing, note it but don't let it block the fix

4.4 Write Regression Test

Write a test that would have caught this bug:

  1. The test should fail WITHOUT the fix (verifying it tests the right thing)
  2. The test should pass WITH the fix
  3. The test should be minimal — test the specific behavior that was broken
  4. Place it in the appropriate test file following project conventions

4.5 Deep Track: Quality Check and Related Issues

Deep track only — skip on quick track.

  1. Load code-quality skill:

    Read ${CLAUDE_PLUGIN_ROOT}/skills/code-quality/SKILL.md
    

    Review the fix against code quality principles.

  2. Check for related issues:

    • Search for the same pattern elsewhere in the codebase:
      Grep for the pattern that caused the bug
      
    • If the same bug exists in other locations, report them to the user
    • Ask via AskUserQuestion: "Fix all related instances now?" / "Fix only the reported bug" / "Create tasks for related fixes"

Phase 5: Wrap-up & Report

Goal: Document the investigation trail and capture learnings.

5.1 Bug Fix Summary

Present to the user:

## Bug Fix Summary

### Bug
[One-line description of the bug]

### Root Cause
[What was actually wrong and why]

### Fix Applied
[What was changed, with file:line references]

### Tests
- [Originally failing test]: Now passing
- [Regression test added]: [test name and location]
- [Related tests]: All passing

### Track
[Quick / Deep] [Escalated from quick: Yes/No]

5.2 Hypothesis Journal Recap

Present the complete hypothesis journal showing the investigation trail:

### Investigation Trail

#### H1: [Title]
- Status: Confirmed / Rejected
- [Key evidence summary]

#### H2: [Title] (if applicable)
- Status: Confirmed / Rejected
- [Key evidence summary]

[... additional hypotheses ...]

5.3 Project Learnings

Load the

project-learnings
skill to evaluate whether this bug reveals project-specific knowledge worth capturing:

Read ${CLAUDE_PLUGIN_ROOT}/skills/project-learnings/SKILL.md

Follow its workflow to evaluate the finding. Common debugging discoveries that qualify:

  • Surprising API behavior specific to this project
  • Undocumented conventions that caused the bug
  • Architectural constraints that aren't obvious from the code

5.4 Deep Track: Future Recommendations

Deep track only:

If the investigation revealed broader concerns, present recommendations:

  • Architecture improvements to prevent similar bugs
  • Missing test coverage areas
  • Documentation gaps
  • Monitoring or alerting suggestions

5.5 Next Steps

Offer the user options via AskUserQuestion:

  • "Commit the fix" — proceed to commit workflow
  • "Review the changes" — show a diff of all modifications
  • "Run full test suite" — run the complete test suite to verify no regressions
  • "Done" — wrap up the session

Hypothesis Journal

The hypothesis journal is the core artifact of this workflow. Maintain it throughout all phases.

Format

## Hypothesis Journal — [Bug Title]

### H1: [Descriptive Title]
- **Hypothesis:** [What's causing the bug — be specific]
- **Evidence for:** [Supporting observations with file:line references]
- **Evidence against:** [Contradicting observations]
- **Test plan:** [Concrete steps to confirm or reject]
- **Status:** Pending / Confirmed / Rejected
- **Notes:** [Additional context, timestamps, agent findings]

### H2: [Descriptive Title]
[Same format]

Rules

  • Minimum hypotheses: 1 on quick track, 2-3 on deep track
  • Never delete entries — rejected hypotheses are valuable context
  • Update incrementally — add evidence as you find it, don't wait
  • Be specific — "the data is wrong" is not a hypothesis; "processOrder receives dollars but expects cents" is

Track Reference

AspectQuick TrackDeep Track
InvestigationRead error location + 1-2 callers2-3 code-explorer agents in parallel
HypothesesMinimum 1Minimum 2-3
Root cause testingManual verification1-3 bug-investigator agents in parallel
Fix validationRun failing + related testsTests + code-quality skill + related issue scan
Auto-escalationAfter 2 rejected hypothesesN/A
Typical complexityOff-by-one, typo, wrong argument, missing null checkRace condition, state corruption, multi-file logic error

Agent Coordination

Code Explorers (Phase 2, deep track)

Use cross-plugin agent reference:

subagent_type: "agent-alchemy-core-tools:code-explorer"

These are Sonnet-model read-only agents that explore codebase areas. Give each a distinct focus area related to the bug. They report structured findings.

Bug Investigators (Phase 3, deep track)

Use same-plugin agent reference:

subagent_type: "bug-investigator"

These are Sonnet-model agents with Bash access for running tests and git commands, but no Write/Edit — they investigate and report evidence, they don't fix code. Give each a specific hypothesis to test.

Error Handling

  • If an agent fails, continue with remaining agents' results
  • If all agents fail in a phase, fall back to manual investigation
  • Never block on a single agent — partial results are better than no results

Error Recovery

If any phase fails:

  1. Explain what went wrong and what you've learned so far
  2. Present the hypothesis journal as-is
  3. Ask the user how to proceed via AskUserQuestion:
    • "Retry this phase"
    • "Skip to fix" (if you have enough evidence)
    • "Provide more context"
    • "Abort"