Individual skill

herdr-swarm

Run a small agent swarm (3-8 workers) through Herdr for large tasks that one agent cannot hold in context — goal decomposition into an ownership-split task tree, merge queue with neutral arbitration, shared decision log, field guide memory, hidden benchmarks. Use when the user wants a swarm, fan-out implementation of a big spec, multi-agent build from a spec, or says swarm/蜂群. Built strictly on top of the herdr-dispatch skill.

skills/herdr-swarm/SKILL.md

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# Herdr Swarm

Small-scale swarm protocol, distilled from Cursor's "Agent swarms and the new model economics" (Jul 2026): scalability comes from **context efficiency and coordination discipline**, not raw parallelism. This skill is the orchestration layer; it never touches `herdr` directly — all spawning, collecting, and messaging goes through the **herdr-dispatch** skill's verbs (`doctor`, `assign`, `watch`, `collect`, `send`, `handoff`, `stop`).

## Preconditions

1. herdr-dispatch must be installed and its `doctor` must pass. If not, stop and tell the human.
2. The task must be big enough that one agent would lose context: multiple modules, a full spec, hours of work. For a single-file fix, use herdr-dispatch directly instead.
3. `--worktree` isolation is mandatory for every implementation leaf. Read-only leaves may share the main tree.

## Roles

- **Captain (this session) = planner.** Decomposes, decides, arbitrates merge order, reviews. The captain never implements code itself and never hand-waves a design decision into a brief — undecided design questions stop the tree until the captain decides them (or asks the human).
- **Workers = executors.** One leaf each. Workers do not plan, do not dispatch, and do not talk to each other. All cross-worker information flows through files the captain points at.
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