Skills

swarm

Installation
SKILL.md

Swarm

Plan first, then launch parallel AI agents that build features AND continuously harden the codebase — all running in isolated Git worktrees.

Workflow

Phase 1: PLAN (interactive, human-in-the-loop)
  ├── Activate grill-me: interrogate the plan until every branch is resolved
  ├── Source the backlog: pull tasks from Linear/GitHub/Jira → local file
  └── Pre-flight checklist: detect tooling, verify setup, confirm configuration

Phase 2: EXECUTE (AFK, multi-agent, overnight)
  └── Dispatcher creates Git worktrees, launches agents in parallel:
      ├── Feature Agent   — TDD through the backlog (subsumes ralph-tdd)
      ├── CRAP Agent      — refactors complex/untested functions
      ├── Mutation Agent   — kills surviving mutants
      └── Acceptance Agent — runs full E2E suite (optional)

Architecture

main ← the integration branch (no agent works here directly)
│
├── .swarm/
│   ├── runs/
│   │   └── 2026-03-04T22-00/
│   │       ├── backlog.md        ← Task list for Feature Agent
│   │       ├── progress.md       ← Structured log of all agent activity
│   │       ├── report.md         ← Summary generated at shutdown
│   │       └── logs/
│   │           ├── feature.log
│   │           ├── crap.log
│   │           ├── mutate.log
│   │           └── accept.log
│   │
│   ├── lessons.md                ← Persists across ALL runs
│   │
│   ├── feature/   ← Git worktree (branch: swarm/feature)
│   ├── crap/      ← Git worktree (branch: swarm/crap)
│   ├── mutate/    ← Git worktree (branch: swarm/mutate)
│   └── accept/    ← Git worktree (branch: swarm/accept)

All four agents work in isolated Git worktrees on their own branches. Main is the shared integration target — agents rebase from main, do their work, and merge back. No agent works directly on main.

Agent Roles

Agent Needs Backlog? Driven By What It Does
Feature ✅ Yes .swarm/runs/<ts>/backlog.md Picks tasks, implements via strict TDD, commits
CRAP ❌ No CRAP score calculator output Finds functions with score > 30, refactors and/or adds tests
Mutation ❌ No Stryker incremental survivor report Finds surviving mutants, writes targeted killing tests
Acceptance ❌ No E2E pass/fail Runs Playwright/Detox, fixes failures or flaky tests

The Feature Agent is backlog-driven. The quality agents are entirely self-directing — their "backlog" IS the metrics output.

Stop Conditions

  • Feature Agent: stops when all tasks in backlog.md are checked off, or max iterations
  • Quality Agents: stop when metrics converge (CRAP < 30 everywhere, mutation ≥ 95%), or max iterations
  • Acceptance Agent: stops when E2E suite passes, or max iterations

Phase 1: Planning

When the user invokes this skill, activate grill-me behavior first:

Interview the user relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one.

Key questions to resolve:

  1. What are we building? Clear description of features/project.
  2. Where is the backlog?
    • Linear — pull issues from a Linear team (use Linear MCP)
    • GitHub Issues — pull from a GitHub repo (gh issue list)
    • Jira — pull from a Jira project
    • Local file — point to an existing PRD, requirements.md, or checklist
    • Create new — build a requirements doc together during planning
  3. Scope and priority? How many tasks? What order?
  4. Acceptance criteria? How do we know each task is done?

Once the plan is resolved, pull tasks from the source and write them to .swarm/runs/<timestamp>/backlog.md as a checklist the Feature Agent will work through. The Feature Agent can reference the remote source (Linear, GitHub) for deeper context on individual tasks, but the local file drives the loop.

Pre-Flight Checklist

After planning, run through all 6 stages before launching. Auto-detect as much as possible, confirm with the user, and fix anything missing.

Stage 1: Project Discovery

# Check How
1 Project root Current directory or --project flag
2 Git state clean? No uncommitted changes
3 Working branch Current branch (becomes integration target)
4 Package manager Detect from lockfile: bun.lockb → bun, pnpm-lock.yaml → pnpm, yarn.lock → yarn, else npm
5 CLAUDE.md exists? If not, create using create-claude-md skill. Agents rely heavily on this.

Stage 2: Backlog

# Check How
6 Backlog source From planning phase
7 Write .swarm/runs/<ts>/backlog.md Pull tasks, write local file
8 Confirm scope and priority Show task list, get user approval

Stage 3: Command Detection

Auto-detect from package.json scripts, then confirm:

# Command Look For
9 Test test, test:unit, vitest
10 Typecheck typecheck, tsc, type-check
11 Lint lint, biome, eslint
12 Coverage test:coverage
13 Mutation test:mutate, test:mutate:incremental
14 E2E test:e2e, e2e

Show detected commands and confirm:

Detected commands (pnpm):
  Test:      pnpm test
  Typecheck: pnpm typecheck
  Lint:      pnpm lint
  Coverage:  pnpm test:coverage
  Mutate:    pnpm test:mutate:incremental
  E2E:       pnpm test:e2e

Correct? Any changes?

Note on Monorepos: The Swarm orchestrator executes scripts from the root package.json. If working in a monorepo (like pnpm workspaces or Turborepo), ensure the root package.json contains proxy scripts (e.g., "test": "pnpm --filter web test", "test:mutate:incremental": "pnpm --filter web test:mutate:incremental") that delegate to the appropriate packages, or else the agents will fail to run verifications.

Stage 4: Tooling Verification

# Check If Missing
15 Coverage outputs lcov.info? Install coverage provider, configure. See Setup
16 Stryker configured? Set up using mutation-testing skill
17 Pre-commit hooks (Husky)? Set up using setup-pre-commit skill
18 Smoke test Run test + typecheck + lint once to verify clean baseline
19 Sub-agent smoke test Run env -u CLAUDECODE claude --version to verify sub-agents can be spawned

Stage 5: Launch Configuration

# Setting Default
20 Which agents? Feature + CRAP + Mutation
21 Include Acceptance agent? Yes if E2E command detected
22 Agent runtime Claude
23 Feature iterations 10
24 Quality iterations 10
25 Auto-merge to main? Yes

Stage 6: Confirm and Launch

Pre-flight complete:
- Project: my-app on branch main (pnpm)
- Backlog: 12 tasks → .swarm/runs/2026-03-04T22-00/backlog.md
- Agents: Feature + CRAP + Mutation (10 iterations each)
- Commands: pnpm test │ typecheck │ lint │ test:coverage │ test:mutate:incremental
- Hooks: ✅ husky pre-commit (lint-staged + typecheck + test)
- Coverage: ✅ v8 → coverage/lcov.info
- Stryker: ✅ incremental mode
- Baseline: ✅ all checks pass

Launch swarm?

Only launch after user confirms.

Configuration (optional)

Swarm can persist project-specific settings so you don't repeat pre-flight every time.

Location: ${CLAUDE_PLUGIN_DATA}/swarm/config.json (stable across skill upgrades)

{
  "defaultBranch": "main",
  "backlogSource": "linear",
  "linearTeam": "TEAM-KEY",
  "agents": ["feature", "crap", "mutate"],
  "featureIterations": 10,
  "qualityIterations": 10,
  "autoMerge": true,
  "simulatorDevice": "iPhone 16",
  "feedbackCommands": {
    "test": "pnpm test",
    "typecheck": "pnpm typecheck",
    "lint": "pnpm lint",
    "coverage": "pnpm test:coverage",
    "mutate": "pnpm test:mutate:incremental",
    "e2e": "pnpm test:e2e"
  }
}

If config exists, pre-flight loads it and shows a summary for confirmation instead of asking each question. Use 'reset' to reconfigure from scratch.

Setup

Coverage (required for CRAP agent)

# Install coverage provider (adapt command to your PM)
npm i -D @vitest/coverage-v8

In vitest.config.ts:

export default defineConfig({
  test: {
    coverage: {
      provider: 'v8',
      reporter: ['text', 'lcov', 'json'],
      reportsDirectory: './coverage',
    },
  },
});

{ "scripts": { "test:coverage": "vitest run --coverage" } }

Stryker (required for Mutation agent)

Use the mutation-testing skill's setup guide. Ensure test:mutate:incremental is configured. Preserve .stryker-incremental.json across runs for faster iteration.

E2E (optional, for Acceptance agent)

Ensure test:e2e runs your Playwright or Detox suite. The swarm is agnostic to which framework — it only calls the npm script.

Pre-commit Hooks

Use the setup-pre-commit skill to configure Husky + lint-staged. This ensures every agent commit passes typecheck + lint + tests before landing.

Running the Swarm

The preferred UX: Do all planning interactively inside the current Claude Code session, and then have Claude launch the swarm directly from this same session (using the shell execution tool). Do NOT ask the user to open a separate terminal.

chmod +x /path/to/skills/swarm/scripts/swarm.sh

# Prefix with 'env -u CLAUDECODE' so that sub-agents can spawn properly!
env -u CLAUDECODE /path/to/skills/swarm/scripts/swarm.sh \
  --project /abs/path/to/your-repo \
  --agents feature,crap,mutate \
  --iterations 10 \
  --agent claude

The script:

  1. Detects your package manager
  2. Creates timestamped run directory
  3. Ensures .swarm/ is added to your project's .gitignore
  4. Creates Git worktrees for each agent
  5. Installs dependencies in each worktree
  6. Launches agents in parallel
  7. Generates report.md on exit (Ctrl+C or all agents done)
  8. Cleans up worktrees

Conflict Resolution

When an agent rebases from main and encounters a merge conflict:

  1. Read the conflict markers (both sides)
  2. Check git log -5 --oneline to understand what the other agent was doing
  3. Read .swarm/runs/<ts>/progress.md for context on recent activity
  4. Resolve the conflict using reasoning about both changes
  5. Run the full test suite to verify the resolution
  6. If tests pass, continue. If tests fail, abort the rebase and retry next iteration.

Gotchas

  • Never commit .swarm/ to git. It is local working state. The script adds it to .gitignore automatically, but verify.
  • Always check backlog is prioritized before launching. An unprioritized backlog means the Feature Agent picks tasks randomly, potentially wasting overnight cycles on low-impact work.
  • Simulator conflicts with multiple agents. If both the Feature Agent and Acceptance Agent need simulators, they'll conflict. Use named simulators with unique UDIDs (see expo-testing skill's parallel isolation section).
  • Verify tests actually ran, not just that they were written. A test file that compiles is not the same as a test that executed against a running app/simulator. Check progress.md for actual execution evidence.
  • Monorepo proxy scripts are required. The swarm orchestrator runs scripts from the root package.json. If working in a monorepo, ensure root scripts delegate to the right package (e.g., "test": "pnpm --filter web test").
  • Stryker incremental JSON must persist. .stryker-incremental.json saves mutation state across runs. If it gets deleted, the Mutation Agent restarts from scratch, wasting hours.
  • Read lessons.md from previous runs. It contains cross-run learnings. Agents should read it at startup to avoid repeating mistakes.
  • Don't start a swarm with failing tests. The pre-flight smoke test exists for a reason. Fix baseline failures before launching — agents will waste cycles trying to fix pre-existing issues.

Progress Tracking

All agents append to .swarm/runs/<ts>/progress.md using a structured format:

# Swarm Progress — 2026-03-04T22:00

## [FEATURE] 22:14 — AUTH-42: User login flow ✅
Files: src/auth/login.ts, login.test.ts · Tests: +3 (47 total) · Commit: a1b2c3d

## [CRAP] 22:15 — processCheckout 142→18 ✅
File: src/checkout/handler.ts · CC: 14→4 · Coverage: 12%→91% · Commit: d4e5f6g

## [MUTATE] 22:17 — src/utils/math.ts killed 5/7 ✅
Score: 88%→94% · Tests: +5 · Commit: h7i8j9k

## [FEATURE] 22:19 — AUTH-43: Password reset ⛔ BLOCKED
Missing SMTP config for email service

This format is both human-scannable and machine-parseable. Agents reference this file to understand what other agents have been doing (useful for conflict resolution).

.swarm/lessons.md persists across runs — agents append patterns and mistakes learned so future runs benefit.

How the CRAP Score Works

CRAP = Change Risk Anti-Patterns. Combines cyclomatic complexity with test coverage.

Formula: CRAP(fn) = CC² × (1 - cov)³ + CC

CRAP Score Meaning
1–5 Clean — low complexity, well tested
5–30 Moderate — consider refactoring or adding tests
30+ Crappy — high complexity with poor coverage, refactor immediately

The CRAP agent picks the worst function (score > 30) and either:

  • Extracts methods to reduce CC
  • Adds tests to increase coverage
  • Both — split the function AND test the pieces

See scripts/crap4ts.mjs for the calculator.

On-Demand Hooks

Swarm registers session-scoped hooks that activate when the skill is invoked. These prevent common issues during unattended multi-agent runs.

Registered hooks

{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Bash",
        "command": "echo \"$TOOL_INPUT\" | grep -qE '(rm -rf|git push --force|git reset --hard|DROP TABLE)' && echo 'BLOCK: Destructive command blocked during swarm. Agents should not run destructive operations.' || true"
      },
      {
        "matcher": "Bash",
        "command": "echo \"$TOOL_INPUT\" | grep -qE 'git add \\.' && echo 'BLOCK: Use specific file paths instead of git add . during swarm to avoid committing .swarm/ files.' || true"
      }
    ]
  }
}

These hooks:

  • Block destructive commands during unattended multi-agent runs
  • Block git add . to prevent accidentally committing .swarm/ working state

References

Topic Source Load When
Planning grill-me skill Phase 1 — interrogating the plan
TDD discipline mattpocock/skills@tdd Feature Agent red-green-refactor
Mutation setup mutation-testing skill Pre-flight or Mutation Agent
Pre-commit hooks setup-pre-commit skill Pre-flight Stage 4
CLAUDE.md create-claude-md skill Pre-flight Stage 1
Agent prompts references/agent-prompts.md Phase 2 launch
Worktree lifecycle references/worktree-coordination.md Phase 2 launch
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