spawn
/spawn
Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.
- Author
- alirezarezvani ↗
- Repository
- claude-skills ↗
- Licence
- MIT
- Last repository change
- 23.10.2026
Assessment and security
- Files in this package
- 1
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
- 0
No signals detected. Repository changed on 23.10.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
What it does and when to use it
Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.
Original author description
Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.
How it works
- Usage
- Templates
- What It Does
- Critical Rules
- After Spawn
SKILL.md preview
---
name: "spawn"
description: "Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session."
metadata:
command: /hub: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 `../agenthub/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:hub-status`
- Evaluate when done with `/hub:eval`
Versions
| Repository | Score | Licence |
|---|---|---|
| This page · alirezarezvani/claude-skills | 100 | MIT |
| howardpark-ai/stackshot-plugin | 100 | MIT |
| koolamusic/claudefiles | 100 | MIT |
| bestagentkits/agency-skills | 100 | MIT |
| bonneted/research-knowledge-tree | 96 | MIT |
| hhoikoo/agent-marketplace | 90 | Apache-2.0 |
Database snapshot: 13.11.2026 · package version 4ae60e4cea25 (SHA-256 digest of the entire package)
Downloads in the last 30 days: 0 · ranking
Report a problem with this skill: harmful content, incorrect descriptions or an author’s removal request.
Similar skills
- 100agenthub
Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in… - 100agenthub
Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in… - 100agent-spawn
Use when launching parallel tmux agents with optional isolated Git worktrees under Oh My Harness. - 100hub-status
Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:hub-status or asks how the AgentHub agents are doing. - 100status
Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:status or asks how the AgentHub agents are doing. - 100run
One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:run or asks to execute a full AgentHub competition end-to-end.