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swarm

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

Skill by uzairansaruzi

IndexedMIT★ 155
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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.

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About

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

Use cases: documents, testing

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What's inside

Skill name
swarm
Description
Fan out N parallel workers, drain them, and return one report. Use for /swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.
License
MIT
Instructions
40 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Swarm

Fan out N parallel 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.
4. Pick the worker model from the `swarm workers` line in `p3-models.md`, resolved through `orchestrator_capabilities`. If the file or that line is missing, run `setup-p3`. For `auto` or `inherit`, omit `target` so the workers run on the parent model. If `delegate_task` rejects the target, fall back to the closest valid model of the same family from `orchestrator_capabilities` and say so. For a model race, name each arm's model up front.
5. 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

Spawn all N workers in one turn with `delegate_task`, `mode: "async"`, and the step 4 target, left unset for `auto` or `inherit`. Use `t3_thread_launch` with a `workspaceStrategy` only when a worker needs its own thread, worktree, or branch. One writer per worktree.

Every brief stands alone. Child agents get only the brief, never the parent's context. Include the goal, scope, exact slice or race arm, how to verify, and what to report. Reports use `PASS`, `ISSUES`, or `BLOCKED` with evidence. A worker that can prove a defect reports `ISSUES` and lists every issue it can prove, not only the first.

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

## Phase C: Aggregate

Drain with `task_status` until every worker is terminal. Drop a result that does not record the SHAs and method its brief names, and respawn that worker once. After a second miss, record a gap. A gap does not count as a pass. 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 uzairansaruzi/p3-stack, MIT.

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Signals

Stars
155
Forks
21
Open issues
1
Last commit (this folder)
Oct 5, 2026 (25 days 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/uzairansaruzi-swarm (last updated 2026-10-24)