# Spawn

> Launch N parallel subagents in isolated git worktrees to compete on the session task.

- Skill: `neekware/spawn` (Agent Skill)
- Install (CLI): `npx skillmds add neekware/spawn`
- Raw SKILL.md: https://api.skillmd.com/api/skills/neekware/spawn/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: neekware (https://skillmd.com/u/neekware)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/neekware/spawn

---


# /hub:spawn — Launch Parallel Agents

Spawn N subagents that work on the same task in parallel, each in an isolated git worktree.

## Usage

```
/hub:spawn                                    # Spawn agents for the latest session
/hub:spawn 20260317-143022                    # Spawn agents for a specific session
/hub:spawn --template optimizer               # Use optimizer template for dispatch prompts
/hub:spawn --template refactorer              # Use refactorer template
```

## Templates

When `--template <name>` is provided, use the dispatch prompt from `references/agent-templates.md` instead of the default prompt below. Available templates:

| Template      | Pattern                                  | Use Case                             |
| ------------- | ---------------------------------------- | ------------------------------------ |
| `optimizer`   | Edit → eval → keep/discard → repeat x10  | Performance, latency, size reduction |
| `refactorer`  | Restructure → test → iterate until green | Code quality, tech debt              |
| `test-writer` | Write tests → measure coverage → repeat  | Test coverage gaps                   |
| `bug-fixer`   | Reproduce → diagnose → fix → verify      | Bug fix with competing approaches    |

When using a template, replace all `{variables}` with values from the session config. Assign each agent a **different strategy** appropriate to the template and task — diverse strategies maximize the value of parallel exploration.

## What It Does

1. Load session config from `.agenthub/sessions/{session-id}/config.yaml`
2. For each agent 1..N:
   - Write task assignment to `.agenthub/board/dispatch/`
   - Build agent prompt with task, constraints, and board write instructions
3. Launch ALL agents in a **single message** with multiple Agent tool calls:

```
Agent(
  prompt: "You are agent-{i} in hub session {session-id}.

Your task: {task}

Read your full assignment at .agenthub/board/dispatch/{seq}-agent-{i}.md

Instructions:
1. Work in your worktree — make changes, run tests, iterate
2. Commit all changes with descriptive messages
3. Write your result summary to .agenthub/board/results/agent-{i}-result.md
   Include: approach taken, files changed, metric if available, confidence level
4. Exit when done

Constraints:
- Do NOT read or modify other agents' work
- Do NOT access .agenthub/board/results/ for other agents
- Commit early and often with descriptive messages
- If you hit a dead end, commit what you have and explain in your result",
  isolation: "worktree"
)
```

4. Update session state to `running` via:

```bash
python {skill_path}/scripts/session_manager.py --update {session-id} --state running
```

## Critical Rules

- **All agents in ONE message** — spawn all Agent tool calls simultaneously for true parallelism
- **isolation: "worktree"** is mandatory — each agent needs its own filesystem
- **Never modify session config** after spawn — agents rely on stable configuration
- **Each agent gets a unique board post** — dispatch posts are numbered sequentially

## After Spawn

Tell the user:

- {N} agents launched in parallel
- Each working in an isolated worktree
- Monitor with `/hub:status`
- Evaluate when done with `/hub:eval`