Agent skill

swarm-coordination

Multi-agent swarm coordination patterns. Orchestrates parallel agent execution, manages agent communication, handles task distribution, and coordinates results aggregation.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/swarm-coordination

SKILL.md

Swarm Coordination Skill

Step 1: Analyze Task for Parallelization

Identify parallelizable work:

Pattern Example Strategy
Independent tasks Review multiple files Spawn in parallel
Dependent tasks Design → Implement Sequential spawn
Fan-out/Fan-in Multiple reviews → Consolidate Parallel + Aggregation
Pipeline Parse → Transform → Validate Sequential handoff

Step 2: Spawn Agents in Parallel

Use the Task tool to spawn multiple agents in a single message:

javascript
// Spawn multiple agents in ONE message for parallel execution
Task({
  subagent_type: 'general-purpose',
  description: 'Architect reviewing design',
  prompt: 'Review architecture...',
});

Task({
  subagent_type: 'general-purpose',
  description: 'Security reviewing design',
  prompt: 'Review security...',
});

Key: Both Task calls must be in the SAME message for true parallelism.

Step 3: Define Handoff Format

Use structured formats for agent communication:

markdown
## Agent Handoff: [Source] → [Target]

### Context

- Task: [What was done]
- Files: [Files touched]

### Findings

- [Key finding 1]
- [Key finding 2]

### Recommendations

- [Action item 1]
- [Action item 2]

### Artifacts

- [Path to artifact 1]
- [Path to artifact 2]

Step 4: Aggregate Results

Combine outputs from parallel agents:

markdown
## Swarm Results Aggregation

### Participating Agents

- Architect: Completed ✅
- Security: Completed ✅
- DevOps: Completed ✅

### Consensus Points

- [Point all agents agree on]

### Conflicts

- [Point agents disagree on]
- Resolution: [How to resolve]

### Combined Recommendations

1. [Prioritized recommendation]
2. [Prioritized recommendation]

Step 5: Handle Failures

Strategies for partial failures:

Scenario Strategy
Agent timeout Retry with simpler prompt
Agent error Continue with available results
Conflicting results Use consensus-voting skill
Missing critical result Block and retry

</execution_process>

<best_practices>

  1. Parallelize Aggressively: Independent work should run in parallel
  2. Structured Handoffs: Use consistent formats for communication
  3. Graceful Degradation: Continue with partial results when safe
  4. Clear Aggregation: Combine results systematically
  5. Track Provenance: Know which agent produced each result

</best_practices>

Get architecture, security, and performance reviews for the new API design

Swarm Coordination:

javascript
// Spawn 3 reviewers in parallel (single message)
Task({ description: 'Architect reviewing API', prompt: '...' });
Task({ description: 'Security reviewing API', prompt: '...' });
Task({ description: 'Performance reviewing API', prompt: '...' });

Aggregated Results:

markdown
## API Design Review (3 agents)

### Consensus

- RESTful design is appropriate
- Need authentication on all endpoints

### Recommendations by Priority

1. [HIGH] Add rate limiting (Security)
2. [HIGH] Use connection pooling (Performance)
3. [MED] Add versioning to URLs (Architect)

</usage_example>

Rules

  • Always spawn independent agents in parallel
  • Use structured handoff formats
  • Handle partial failures gracefully

Related Workflow

This skill has a corresponding workflow for complex multi-agent scenarios:

  • Workflow: .claude/workflows/enterprise/swarm-coordination-skill-workflow.md
  • When to use workflow: For massively parallel task execution with Queen/Worker topology, fault tolerance, and distributed coordination (large-scale refactoring, parallel code review, multi-file implementation)
  • When to use skill directly: For simple parallel agent spawning or when integrating swarm patterns into other workflows

Workflow Integration

This skill powers multi-agent orchestration patterns across the framework:

Router Decision: .claude/workflows/core/router-decision.md

  • Router uses swarm patterns for parallel agent spawning
  • Planning Orchestration Matrix defines when to use swarm coordination

Artifact Lifecycle: .claude/workflows/core/skill-lifecycle.md

  • Swarm patterns apply to artifact creation at scale
  • Parallel validation of multiple artifacts

Related Workflows:

  • consensus-voting skill for resolving conflicting agent outputs
  • context-compressor skill for aggregating parallel results
  • Enterprise workflows in .claude/workflows/enterprise/ use swarm patterns

Memory Protocol (MANDATORY)

Before starting:

bash
cat .claude/context/memory/learnings.md

After completing:

  • New pattern -> .claude/context/memory/learnings.md
  • Issue found -> .claude/context/memory/issues.md
  • Decision made -> .claude/context/memory/decisions.md

ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.

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