| name | spawn |
| description | Launch N parallel subagents in isolated git worktrees to compete on the session task. |
| compatibility | opencode |
/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
- Load session config from
.agenthub/sessions/{session-id}/config.yaml
- For each agent 1..N:
- Write task assignment to
.agenthub/board/dispatch/
- Build agent prompt with task, constraints, and board write instructions
- 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"
)
- Update session state to
running via:
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
