Skills

Swarm

Fan out N parallel workers, drain them, and return one report.

Install

npx skills add michael-denyer/pstack-claude --skill swarm -g -a claude-code -y
Category
Engineering
Updated
5d ago
License
MIT
Context cost
Lightabout 1,052 tokens
Runs scripts
No, instructions only

What it does

Fan out N parallel workers, drain them, and return one report. Use for /swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.

Swarm

On Codex, read the platform mapping, including its per-skill notes, before following this skill.

On GitHub Copilot, read the platform mapping, including its per-skill notes, before following this skill.

On Muse, read the platform mapping, including its per-skill notes, before following this skill.

Start

Open a todolist with one entry per phase before launching anything.

  1. Frame
  2. Fan out
  3. Aggregate
  4. Report

Phase A: Frame

  1. State the done predicate and the artifact or report the swarm must return.
  2. Choose the shape. Partition into slices, race N workers on identical briefs, or mix both. For a race or mixed shape, declare first pass, rank all, or best-of before spawning.
  3. Pick the worker model from the swarm workers line in pstack-models.md. If the sheet or that line is missing, use the default in Models. For auto or inherit-parent, omit model so the workers run on the parent model. If the Agent tool rejects a slug, use the default and say so. If it rejects the default, use the closest valid slug of the same family from its error message. For a model race, name each arm's model up front. Pick each subagent's reasoning level for the job, per the Subagents section of the poteto-mode skill.
  4. Give each worker its own writable output when it writes. When workers verify or measure commits, each brief names the exact SHAs. A measurement brief also names the method (sample count, what one sample is, order). The worker records both in its result.

Phase B: Fan out

Read the whole SKILL.md on GitHub

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