Spawn N subagents that work on the same task in parallel, each in an isolated git worktree.
/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
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.
.agenthub/sessions/{session-id}/config.yaml
.agenthub/board/dispatch/
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"
)
running via:python {skill_path}/scripts/session_manager.py --update {session-id} --state running
Tell the user:
/hub:status
/hub:eval