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swarm

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

Skill by kkgogogo17

IndexedMIT★ 10
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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/kkgogogo17-swarm

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About

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

Use cases: documents, testing

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Permissions

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

Tools
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Secrets
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Install scripts
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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 parallel workers, drain them, and return one report. Use for /skill:swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.
License
MIT
Instructions
42 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Swarm

Fan out N parallel cloud 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. Pick the worker model from `swarm workers` in `~/.pi/agent/pstack/models.json` when present. Otherwise use `inherit-parent`. For a model race, name each arm's model 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

Spawn all N workers in one parallel `subagent` call using its `tasks` array. Use `agent: "poteto-agent"` unless a workflow names another agent, and set `role: "swarm workers"`. Pi child processes run locally with isolated context, so give each task explicit file pointers and prevent concurrent writes to shared paths.

When a worker must start from a non-default pushed branch, pass `cloud_base_branch`.

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 kkgogogo17/pi-pstack, MIT.

More from kkgogogo17/pi-pstack

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Stars
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Forks
7
Open issues
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Last commit (this folder)
Aug 8, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

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

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Cite this page

swarm skill. Agent Mart. https://agentmart.dev/skills/kkgogogo17-swarm (last updated 2026-10-24)