Swarm Skill
Spawn isolated agents to execute tasks in parallel. Fresh context per agent (Ralph Wiggum pattern).
Loop position
Move 5 (wave execution) of the operating loop, specifically the parallel-fork primitive /crank invokes. Refuses to spawn parallel agents on a wave that has not cleared the wave-validity check in the slice validation plan: write scopes must be disjoint, no shared migration/contract/CLI surface, integration order declared when it matters, one owner per slice, discard path per slice. Parallelism is explicit ownership, not swarm chaos. Default to sequential when the wave-validity rows are not all green.
Integration modes:
- Direct - Create TaskList tasks, invoke
/swarm - Via Crank -
/crankcreates tasks from beads, invokes/swarmfor each wave
Requires multi-agent runtime. Swarm needs a runtime that can spawn parallel subagents. If unavailable, work must be done sequentially in the current session.
Architecture (Mayor-First)
Mayor (this session)
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+-> Plan: TaskCreate with dependencies
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+-> Identify wave: tasks with no blockers
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+-> Select spawn backend (gc if available; runtime-native: Claude teams in Claude runtime, Codex sub-agents in Codex runtime; fallback tasks if unavailable)
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+-> Assign: TaskUpdate(taskId, owner="worker-<id>", status="in_progress")
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+-> Spawn workers via selected backend
| Workers receive pre-assigned task, execute atomically
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+-> Wait for completion (wait() | SendMessage | TaskOutput)
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+-> Validate: Review changes when complete
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+-> Cleanup backend resources (close_agent | TeamDelete | none)
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+-> Repeat: New team + new plan if more work needed
Execution
Read references/execution-steps.md when you need the full procedural detail (Steps 0–6): backend detection, gc dispatch, task typing + file manifests, context briefing, manifest auto-population, advisory bead clustering, wave identification, pre-spawn conflict check, test-file naming validation, multi-wave base-SHA refresh, and worker dispatch.
Every TaskCreate must include metadata.issue_type plus a metadata.files array.
Do not spawn workers with overlapping file manifests into the same shared-worktree wave.
Example Flow
Mayor: "Let's build a user auth system"
1. /plan -> Creates tasks:
#1 [pending] Create User model
#2 [pending] Add password hashing (blockedBy: #1)
#3 [pending] Create login endpoint (blockedBy: #1)
#4 [pending] Add JWT tokens (blockedBy: #3)
#5 [pending] Write tests (blockedBy: #2, #3, #4)
2. /swarm -> Spawns agent for #1 (only unblocked task)
3. Agent #1 completes -> #1 now completed
-> #2 and #3 become unblocked
4. /swarm -> Spawns agents for #2 and #3 in parallel
5. Continue until #5 completes
6. /vibe -> Validate everything
Scope-Escape Protocol
When a worker discovers work outside their assigned scope, they MUST NOT modify files outside their file manifest. Instead, append to .agents/swarm/scope-escapes.jsonl:
{"worker": "<worker-id>", "finding": "<description>", "suggested_files": ["path/to/file"], "timestamp": "<ISO8601>"}
For richer scope-escape narration (status classification, concrete next step, evidence), see references/scope-escape-template.md. Use the template when a single-line JSONL entry is insufficient for the operator to act on.
The lead reviews scope escapes after each wave and creates follow-up tasks as needed.
Key Points
- Runtime-native local mode - Auto-selects the native backend for the current runtime (gc pool, Claude teams, or Codex sub-agents)
- Universal orchestration contract - Same swarm behavior across Claude and Codex sessions
- Pre-assigned tasks - Mayor assigns tasks before spawning; workers never race-claim
- Fresh worker contexts - New sub-agents/teammates per wave preserve Ralph isolation
- Wave execution - Only unblocked tasks spawn
- Mayor orchestrates - You control the flow, workers write results to disk
- Thin results - Workers write
.agents/swarm/results/<id>.json, orchestrator reads files (NOT Task returns or SendMessage content) - Retry via message/input - Use
send_input(Codex) orSendMessage(Claude) for coordination only - Atomic execution - Each worker works until task done
- Graceful degradation - If multi-agent unavailable, work executes sequentially in current session
Workflow Integration
This ties into the full workflow:
/research -> Understand the problem
/plan -> Decompose into beads issues
/crank -> Autonomous epic loop
+-- /swarm -> Execute each wave in parallel
/vibe -> Validate results
/post-mortem -> Extract learnings
Direct use (no beads):
TaskCreate -> Define tasks
/swarm -> Execute in parallel
The knowledge flywheel captures learnings from each agent.
Task Management Commands
# List all tasks
TaskList()
# Mark task complete after notification
TaskUpdate(taskId="1", status="completed")
# Add dependency between tasks
TaskUpdate(taskId="2", addBlockedBy=["1"])
Parameters
| Parameter | Description | Default |
|---|---|---|
--max-workers=N | Max concurrent workers | 5 |
--from-wave <json-file> | Load wave from OL hero hunt output (see OL Wave Integration) | - |
--per-task-commits | Commit per task instead of per wave (for attribution/audit) | Off (per-wave) |
When to Use Swarm
| Scenario | Use |
|---|---|
| Multiple independent tasks | /swarm (parallel) |
| Sequential dependencies | /swarm with blockedBy |
| Mix of both | /swarm spawns waves, each wave parallel |
Why This Works: Ralph Wiggum Pattern
Follows the Ralph Wiggum Pattern: fresh context per execution unit.
- Wave-scoped worker set = spawn workers -> execute -> cleanup -> repeat (fresh context each wave)
- Mayor IS the loop - Orchestration layer, manages state across waves
- Workers are atomic - One task, one spawn, one result
- TaskList as memory - State persists in task status, not agent context
- Filesystem for EVERYTHING - Code artifacts AND result status written to disk, not passed through context
- Backend messaging for signals only - Short coordination signals (under 100 tokens), never work details
Ralph alignment source: ../shared/references/ralph-loop-contract.md.
Integration with Crank
When /crank invokes /swarm: Crank bridges beads to TaskList, swarm executes with fresh-context agents, crank syncs results back.
| You Want | Use | Why |
|---|---|---|
| Fresh-context parallel execution | /swarm | Each spawned agent is a clean slate |
| Autonomous epic loop | /crank | Loops waves via swarm until epic closes |
| Just swarm, no beads | /swarm directly | TaskList only, skip beads |
| RPI progress gates | /ratchet | Tracks progress; does not execute work |
OL Wave Integration
Read references/ol-wave-integration.md when you invoke /swarm --from-wave <json-file> — covers pre-flight ol CLI check, input JSON format, task creation from wave entries, completion backflow via ol hero ratchet, and example flow.
References
- Executable acceptance: references/swarm.feature — wave-validity gate, fresh-context workers, conflict-free ownership, results+cleanup (soc-qk4b)
- Local Mode Details:
skills/swarm/references/local-mode.md - Validation Contract:
skills/swarm/references/validation-contract.md
Examples
Building a User Auth System
User says: /swarm
What happens:
- Agent identifies unblocked tasks from TaskList (e.g., "Create User model")
- Agent selects spawn backend usin