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swarm

Fan out N independent workers, collect their results, and return one report for coverage, races, gauntlets, or exploration.

Skill by painhardcore

IndexedMIT★ 12
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/painhardcore-swarm

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Fan out N independent workers, collect their results, and return one report for coverage, races, gauntlets, or exploration.

Use cases: documents, testing

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/swarm

What's inside

Skill name
swarm
Description
Fan out N independent workers, collect their results, and return one report for coverage, races, gauntlets, or exploration.
License
MIT
Instructions
42 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Swarm

Fan out N independent workers. They may cover separate slices, race the same brief, or mix both. The parent waits, aggregates, and returns one report.

## 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. Set N from the user or derive it from the shape. N is total workers, not the cloud concurrency limit.
4. Inherit the parent model unless the host supports model selection and the race explicitly compares models. Name each model-race arm up front.
5. Give each worker its own writable output when it writes. Use a worktree, branch, or `/tmp/swarm-<slug>/worker-<n>/`.

## Phase B: Fan out

Use the host's native subagent tool to start all N workers concurrently. Give each worker the minimum file and tool access its slice needs. If subagents are unavailable or forbidden, run each slice inline and preserve the same result schema.

When a worker needs a non-default branch, name that branch in its brief and use an isolated checkout or worktree.

Every brief stands alone. Include the goal, scope, exact slice or race arm, how to verify, and what to report. Reports use `PASS`, `ISSUES`, or `BLOCKED` with evidence.

If a worker drops out, proceed with N-1 and note it.

## Phase C: Aggregate

Read the terminal results. For coverage, every required slice needs a result. For a race, apply the selection rule declared up front. Use first pass, rank all, or best-of. Do not paste raw worker dumps.

Keep a compact result table, one-line evidenced issues, and explicit gaps or dropouts.

## Phase D: Report

Return one consolidated in-chat report with the table, issue one-liners, gaps or dropouts, and the race rule when used.

From painhardcore/pstack, MIT.

More from painhardcore/pstack

Signals

Stars
12
Forks
3
Open issues
0
Last commit (this folder)
Aug 27, 2026 (2 months ago)
Last release
Aug 26, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from painhardcore

Cite this page

swarm skill. Agent Mart. https://agentmart.dev/skills/painhardcore-swarm (last updated 2026-10-24)