ds-swarm
Skill80 starsChanged 15 days agoMITView on GitHub
Fan out N parallel workers on slices of a job or on a race, collect every result, and return one evidence-backed report. Use for wide coverage, audits, races between approaches or exploration, or for /ds-swarm, 'swarm this', 'split this across workers'.
In this repository28 other files it gives its agents.
- ds-adoptSkill
- ds-best-of-nSkill
- ds-blast-radiusSkill
- ds-blueprintSkill
- ds-catchupSkill
- ds-context-resetSkill
- ds-design-auditSkill
- ds-designSkill
- ds-explainSkill
- ds-helpSkill
- ds-jurySkill
- ds-ledgerSkill
- ds-lessonsSkill
- ds-modeSkill
- ds-plan-loopSkill
- ds-pr-commentsSkill
- ds-principlesSkill
- ds-prSkill
- ds-readySkill
- ds-review-loopSkill
- ds-reviveSkill
- ds-sharpenSkill
- ds-shipSkill
- ds-tddSkill
- ds-unslopSkill
- ds-unstickSkill
- ds-verify-loopSkill
- ds-watch-prSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
Write one brief per worker that stands alone: goal, exact slice, how to verify, what to report.
- Distinctive: line 23
Every slice has a result or a recorded gap and the report is written.
- Distinctive: line 25
Never respawn a worker more than once.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
ds-swarm
Split work that is wide but shallow across parallel workers, then merge their proven results into one report.
Steps
- State the done condition and the report the swarm must return.
- Pick the shape. Partition the job into non-overlapping slices, or race N workers on the same brief, or both. For a race, decide up front how you will choose: first pass, rank all, or best one.
- Write one brief per worker that stands alone: goal, exact slice, how to verify, what to report. When workers test specific commits, name the exact commit hashes and the measurement method.
- Give every worker that writes files its own output location.
- Spawn all workers at once. If the harness cannot run subagents, run the briefs one by one in fresh contexts.
- Each worker reports PASS, ISSUES or BLOCKED with evidence: commands run and their output. ISSUES lists every provable issue, not just the first.
- Collect results. Reject any result with no evidence or the wrong commit and respawn that worker once. A second miss is a recorded gap, not a pass.
- Merge into one report: the verdict, each slice or arm with its evidence, gaps, and duplicates merged by root cause.
Stop when
- Every slice has a result or a recorded gap and the report is written.
- Or a race has a winner under the rule from step 2.
- Never respawn a worker more than once.
Rules
- Workers do not share writable state.
- A missing slice is never counted as passing.
- Report what workers proved, not what they claimed.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

