bug-hunt-swarm
Parallel read-only multi-agent root-cause investigation for bugs and regressions. Use when: investigating bugs, finding root causes, tracing regressions, or diagnosing failures with multi-agent swarm.
Best use case
bug-hunt-swarm is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Parallel read-only multi-agent root-cause investigation for bugs and regressions. Use when: investigating bugs, finding root causes, tracing regressions, or diagnosing failures with multi-agent swarm.
Teams using bug-hunt-swarm should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/bug-hunt-swarm/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How bug-hunt-swarm Compares
| Feature / Agent | bug-hunt-swarm | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Parallel read-only multi-agent root-cause investigation for bugs and regressions. Use when: investigating bugs, finding root causes, tracing regressions, or diagnosing failures with multi-agent swarm.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Bug Hunt Swarm Investigate a bug with four read-only sub-agents in parallel, then have the main agent rank the likely causes and recommend the fastest path to prove or fix the issue. This skill is diagnosis-first: do not edit files or implement fixes as part of this workflow. ## Step 1: Build the Bug Packet Start by collecting the smallest useful investigation packet: 1. Symptom 2. Expected behavior 3. Actual behavior 4. Reproduction steps, if known 5. Scope of impact 6. Relevant evidence, such as logs, stack traces, failing tests, screenshots, recent diffs, or environment details Prefer this source order: 1. Direct user description 2. Explicit files, stack traces, logs, tests, or screenshots provided by the user 3. Current git changes or recent repo history when the bug appears regression-like 4. The smallest relevant code path or subsystem surrounding the failure If the bug report is underspecified, infer a minimal problem statement and say what is still unknown. Before launching sub-agents, read the closest project instructions and relevant docs for the touched area, such as: - `AGENTS.md` - repo workflow docs - architecture, state, routing, schema, or runtime docs for the affected subsystem ## Step 2: Bound the Investigation Write a short investigation brief for the swarm: 1. What appears broken 2. What is not yet proven 3. What part of the system is most likely involved 4. What evidence already exists 5. What kind of proof would count as confirmation Use read-only evidence gathering where useful: - `rg`, `git diff`, `git log`, `git show` - reading logs, crash traces, and config - existing test runs or the smallest safe reproduction command Do not edit files, inject new instrumentation, or implement fixes as part of this skill. ## Step 3: Launch Four Read-Only Investigators in Parallel Launch four sub-agents when the problem is large or ambiguous enough that parallel investigation helps. For a tiny and obvious issue, it is acceptable to investigate locally instead. For every sub-agent: - give the same bug packet and investigation brief - state that the sub-agent is read-only - do not let the sub-agent edit files, run `apply_patch`, stage changes, commit, or perform any other state-mutating action - ask for concise investigation output only - ask for: hypothesis, supporting evidence, missing evidence, smallest proof step, and confidence - tell the sub-agent to avoid generic code quality feedback, nits, or speculative guesses without evidence - tell the sub-agent to send findings back to the main agent only Use these four investigation roles. ### Sub-Agent 1: Reproduction and Scope Investigation Clarify the exact failure shape and its boundaries. Check for: 1. The narrowest reliable trigger 2. Conditions that make the bug appear or disappear 3. Expected versus actual behavior at the failure boundary 4. Whether the impact is local, cross-cutting, deterministic, or flaky This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes. Recommended sub-agent role: `reviewer` ### Sub-Agent 2: Code Path and Failure Seam Investigation Trace the most likely execution path and identify the seam where behavior diverges. Check for: 1. State transitions, lifecycle edges, or ordering problems 2. Mismatched assumptions between caller and callee 3. Data-flow or control-flow breaks 4. The smallest code region most likely responsible for the failure This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes. Recommended sub-agent role: `explorer` for broad tracing, or `reviewer` when a stronger local reasoning pass is more useful ### Sub-Agent 3: Recent Change and Regression Investigation Look for likely regressors in nearby history or changed contracts. Check for: 1. Recent diffs that correlate with the symptom 2. Config, flag, dependency, schema, or migration drift 3. Partial updates where several entry points should have changed together 4. Behavior changes that fit the timing of the bug report This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes. Recommended sub-agent role: `reviewer` ### Sub-Agent 4: Proof Plan and Observability Investigation Determine the fastest way to confirm or reject the leading hypotheses. Check for: 1. The smallest existing test or reproduction that should fail 2. The most useful current logs, traces, metrics, or assertions 3. A minimal non-mutating command that could raise confidence quickly 4. What evidence is missing and how to collect it without broad churn This sub-agent is read-only. It must not edit files, apply patches, or make any other workspace changes. Recommended sub-agent role: `reviewer` Report only hypotheses that materially improve the odds of finding the real cause. It is better to return two evidence-backed theories than six vague guesses. ## Step 4: Synthesize Ranked Hypotheses The main agent owns synthesis. Treat sub-agent output as raw investigation input, not final output. Merge and rank the hypotheses: - combine duplicates - discard weak speculation - prefer evidence over elegance - separate likely root causes from mere contributing factors - keep alternate theories only when they remain plausible Normalize the surviving hypotheses into this shape: 1. Hypothesis 2. Supporting evidence 3. Missing or conflicting evidence 4. Smallest proof step 5. Confidence: high, medium, or low If the evidence is too weak for a real ranking, say so directly and present the leading open questions instead. ## Step 5: Output a Clear Diagnosis Path Present the result in this order: 1. Most likely root cause 2. Plausible alternate causes, if any 3. Fastest proof step 4. Recommended fix path 5. Open questions or blockers When the fix is not yet clear, recommend the next proving step instead of pretending the diagnosis is complete. When helpful, group actions into: - `prove now` - `fix next` - `follow up later` Do not implement fixes as part of this skill. The output is a read-only diagnosis with a prioritized path forward.
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