| name | swarm |
| description | Runs tasks via Map-Reduce, Consensus, or Relay swarms. Triggers: swarm, map-reduce, consensus swarm, relay swarm, parallel agents. |
| user-invocable | true |
| effort | max |
| argument-hint | [map-reduce|consensus|relay] [--with-kb] [--worktree] [task] |
| context | fork |
| agent | orchestrator |
| model | opus |
| allowed-tools | Bash, Read, Write, Edit, Glob, Grep, Agent, TeamCreate, TeamDelete, SendMessage, TaskCreate, TaskList, TaskUpdate, TaskGet, TaskOutput, TaskStop |
/swarm - Parallel Agent Swarm
$ARGUMENTS
MANDATORY: You MUST use the Agent tool
DO NOT do the work yourself. Decompose the task and invoke agents via multiple parallel Agent tool calls. Single-agent execution = failure.
Modes
Map-Reduce (default)
Split task into N independent sub-tasks. Launch ALL agents in a single response (parallel execution).
# Single response with N Agent tool calls:
Agent(subagent_type="...", prompt="sub-task 1 — own files: path/a/")
Agent(subagent_type="...", prompt="sub-task 2 — own files: path/b/")
Agent(subagent_type="...", prompt="sub-task N — own files: path/n/")
After all complete: aggregate results (see Aggregation section below), produce synthesis report.
Consensus
Same problem, 3 independent agents from different angles. Launch all 3 in a single response.
Agent(subagent_type="backend-specialist", prompt="[problem] — approach from data layer angle. Output: solution + confidence 0.0–1.0")
Agent(subagent_type="tech-lead", prompt="[problem] — approach from architecture angle. Output: solution + confidence 0.0–1.0")
Agent(subagent_type="performance-optimizer", prompt="[problem] — approach from performance angle. Output: solution + confidence 0.0–1.0")
After all complete: pick winner by confidence score, note dissents.
Relay
Sequential chain — each agent depends on the previous output. Launch one at a time, wait for completion before next.
# Round 1
Agent(subagent_type="tech-lead", prompt="Design the API spec. Output to docs/api-spec.md")
# Wait for completion
# Round 2
Agent(subagent_type="backend-specialist", prompt="Implement based on docs/api-spec.md. Own files: src/")
# Wait for completion
# Round 3
Agent(subagent_type="test-engineer", prompt="Write tests for src/. Own files: tests/")
File Ownership Rules (CRITICAL)
Each agent MUST own distinct file paths. No overlapping paths. No exceptions.
Agent Tool Call Format
Agent(
subagent_type="<agent-name>",
description="<3-5 word summary>",
prompt="<full task description including: original request, specific sub-task, owned files, success criteria>"
)
Aggregation (after all agents complete)
- Collect all agent outputs into a uniform format (JSON or Markdown sections)
- De-duplicate identical findings across agents
- Synthesize unique insights into one report
