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kkgogogo17kkgogogo17/pi-pstack/skills/swarm/SKILL.md

swarm

Skill9 starsChanged 3 months agoMITView on GitHub

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

We split this skill into the rules it gives an agent

5 rules. 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 78 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

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

    line 32
  2. Very specific:

    Every brief stands alone. Include the goal, scope, exact slice or race arm, how to verify, and what to report.

    line 34
  3. Distinctive:

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

    line 36
  4. Distinctive:

    Read the terminal results.

    line 40
  5. Distinctive:

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

    line 42

“Common” is measured: kept by at least 6 in 10 of the 78 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.

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