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threnody-swarmlisted

Start and run Threnody execute_swarm with host-native host_spawn_waves, topology selection (dag/star/hierarchical/auto), budget preview, and resume. Use when user asks to swarm, fan out agents, or run multi-agent waves with swarm_id persistence.
timjensgrossinger/threnody · ★ 2 · AI & Automation · score 75
Install: claude install-skill timjensgrossinger/threnody
# Threnody swarm orchestration ## Default: host-native swarms For MCP host callers (Claude, Copilot, Cursor, Codex, etc.), `execute_swarm` defaults to **`host_native`**: 1. Threnody plans the task. 2. Returns `awaiting_host_execution: true` + `host_spawn_waves`. 3. **You** spawn host `Task`/`Agent` per wave — Threnody does not subprocess. This path is **unaffected** by utility-only delegation rules. ## Fast-start contract Agent-emitting swarm paths must return `host_spawn_waves` quickly: target **under 5 seconds** to a spawnable handoff and **under 30 seconds** to first host spawn. Use the fast host-native handoff first; optional refinement, consensus, learning aggregation, and detailed receipts happen after the first worker wave starts or at terminal reporting. Within each wave, spawn every agent as the same batch before waiting on the wave barrier. A host loop that starts one same-wave agent, waits, then starts the next is a fast-start regression. Token discipline applies to all swarm shapes: keep host-native handoff compact, prefer bounded file-level fanout for broad sweeps, and reserve star/consensus or high-tier synthesis for explicit deep-risk work. ## Workflow 0. If not already planned, follow **`threnody-plan`** (plan-only swarm preview stops before spawn). 1. Optionally `route_task` for tier context. 2. **`execute_swarm(task, topology?, max_agents?, budget_limit?)`** 3. Handle response: - **`awaiting_host_execution` + `host_spawn_waves`** — execute waves