smithery.ai

swarm-coordination

Multi-agent coordination patterns for OpenCode swarm workflows. Use when work benefits from parallelization or coordination. Covers: decomposition, worker spawning, file reservations, progress tracking, and review loops.

First seen Apr 10, 2026

Installation

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code opencode

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,768 B
  • docs SUMMARY.md 150 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 6 installs

SKILL.md

Swarm Coordination

This skill guides multi-agent coordination for OpenCode swarm workflows.

When to Use

  • Tasks touching 3+ files
  • Parallelizable work (frontend/backend/tests)
  • Work requiring specialized agents
  • Time-to-completion matters

Avoid swarming for 1–2 file changes or tightly sequential work.

Tool Access (Wildcard)

This skill is configured with tools: ["*"] per user choice. If you need curated access later, replace the wildcard with explicit tool lists.

Foreground vs Background vs Agent Teams

  • Foreground agents can access MCP tools.
  • Background agents do not have MCP tools.
  • Agent Team Teammates (when CLAUDECODEEXPERIMENTALAGENTTEAMS enabled) have independent context and messaging.
  • Use foreground workers for swarmmail, swarm, hive_*, and MCP calls.
  • Use background workers for doc edits and static work only.

MCP Lifecycle

Claude Code auto-launches MCP servers from mcpServers configuration. Do not require manual swarm mcp-serve except for debugging.

Agent teams spawn separate instances with their own MCP connections. Each teammate has independent tool access.

Coordinator Protocol (Dual-Path)

Native Teams (When Available)

  1. Initialize Swarm Mail (swarmmail_init).
  2. Query past learnings (hivemind_find).
  3. Decompose (swarmplanprompt + swarmvalidatedecomposition).
  4. Spawn via TeammateTool for real-time coordination.
  5. Review via native team messaging + swarm_review for persistence.
  6. Record outcomes (swarm_complete).

Fallback (Task Subagents)

  1. Initialize Swarm Mail (swarmmail_init).
  2. Query past learnings (hivemind_find).
  3. Decompose (swarmplanprompt + swarmvalidatedecomposition).
  4. Spawn workers via Task(subagent_type="swarm-worker", prompt="...").
  5. Review worker output (swarmreview + swarmreview_feedback).
  6. Record outcomes (swarm_complete).

Worker Protocol (Dual-Path)

With Agent Teams

  1. Auto-initialize via session-start hook.
  2. Reserve files (swarmmail_reserve) — native teams have NO file locking.
  3. Use TaskUpdate for UI spinners + swarm_progress for persistent tracking.
  4. Complete with swarm_complete (auto-releases reservations).

Without Agent Teams

  1. Initialize Swarm Mail (swarmmail_init).
  2. Reserve files (swarmmail_reserve).
  3. Work within scope and report progress (swarm_progress).
  4. Complete with swarm_complete.

File Reservations

Workers must reserve files before editing and release via swarm_complete. Coordinators never reserve files.

Progress Reporting

Use TaskUpdate for UI spinners (shows instant feedback in Claude Code) and swarm_progress at 25%, 50%, and 75% completion for persistent tracking and auto-checkpoints.

Spawning Workers (CRITICAL - Read This)

Step 1: Prepare the subtask

const spawnResult = await swarm_spawn_subtask({
  bead_id: "cell-abc123",           // The hive cell ID for this subtask
  epic_id: "epic-xyz789",           // Parent epic ID
  subtask_title: "Add logging utilities",
  subtask_description: "Create a logger module with structured logging support",
  files: ["src/utils/logger.ts", "src/utils/logger.test.ts"],  // Array of strings, NOT a JSON string
  shared_context: "This epic is adding observability. Other workers are adding metrics and tracing.",
  project_path: "/absolute/path/to/project"  // Required for tracking
});

Step 2: Spawn the worker with Task

// Parse the result to get the prompt
const { prompt, recommended_model } = JSON.parse(spawnResult);

// Spawn the worker
await Task({
  subagent_type: "swarm:worker",
  prompt: prompt,
  model: recommended_model  // Optional: use the auto-selected model
});

Common Mistakes

WRONG - files as JSON string:

files: '["src/auth.ts"]'  // DON'T do this

CORRECT - files as array:

files: ["src/auth.ts", "src/auth.test.ts"]  // Do this

WRONG - missing project_path:

swarm_spawn_subtask({
  bead_id: "...",
  epic_id: "...",
  // No project_path - worker can't initialize tracking!
})

CORRECT - include project_path:

swarm_spawn_subtask({
  bead_id: "...",
  epic_id: "...",
  project_path: "/Users/joel/myproject"  // Required!
})

Parallel vs Sequential Spawning

Parallel (independent tasks)

Send multiple Task calls in a single message:

// All in one message - runs in parallel
Task({ subagent_type: "swarm:worker", prompt: prompt1 })
Task({ subagent_type: "swarm:worker", prompt: prompt2 })
Task({ subagent_type: "swarm:worker", prompt: prompt3 })

Sequential (dependent tasks)

Await each before spawning next:

const result1 = await Task({ subagent_type: "swarm:worker", prompt: prompt1 });
// Review result1...
const result2 = await Task({ subagent_type: "swarm:worker", prompt: prompt2 });

Story Status Flow

Status transitions should flow:

  1. Coordinator sets story to in_progress when spawning worker
  2. Worker completes work and sets to readyforreview
  3. Coordinator reviews and sets to passed or failed

Workers do NOT set final status - that's the coordinator's job after review.

Skill Loading Guidance

Workers should load skills based on task type:

  • Tests or fixes → testing-patterns
  • Architecture → system-design
  • CLI work → cli-builder
  • Coordination → swarm-coordination