swarm
Skill2 starsChanged 6 days agoMITView on GitHub
Runs several fresh agents on one artifact, one lens each, and merges their evidence into a verdict table; in teardown mode it also verifies, answers and fixes every finding. Use when asked for an agent swarm, several reviewers, a multi-agent review, or to tear down or find everything wrong with a diff, plan, design or document.
87 other projects use a version of this.
Adopted by
Most recently taken up by
- endqwerty/endstacktheir own version, first seen Nov 8, 2026
- tristanphvn/keeltheir own version, first seen Nov 8, 2026
- hidenobunagai/astacktheir own version, first seen Nov 8, 2026
- Belweave/hstacktheir own version, first seen Nov 8, 2026
- blinkboxhq/Blinkboxtheir own version, first seen Nov 8, 2026
- requie/endostacktheir own version, first seen Nov 8, 2026
Used with
Projects with it also use poteto-help, make-bot-ui and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
ianclearySkillpoteto-help
Guides users through pstack setup, /poteto-mode, and picking the skill, playbook, or principle for a task. Type /poteto-help with a question.
Also in 14 projects that use this
eryzerzSkillmake-bot-ui
Use when building a custom UI (page, dashboard, buttons) that should wake a Grok Bot over a webhook, when the user must provide a webhook sender key, or when exposing that UI on Tailscale.
Also in 19 projects that use this
ianclearySkillprinciple-explain-the-number
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Also in 27 projects that use this
bnemaSkillsetup-pstack
Configure which Pi models pstack uses per role. Detects available provider/model specs and writes pstack's user configuration. Use for /setup-pstack, "configure pstack models", or changing pstack model choices.
Also in 23 projects that use this
jaydubya818Skillprinciple-attack-the-premise
Apply when repeated fixes fail and a shared assumption may be wrong.
Also in 31 projects that use this
jaydubya818Skillpoteto-mode
Use when non-trivial work should follow the smallest rigorous Jstack workflow.
Also in 27 projects that use this
- +5 more from jaydubya818
Other versions87 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 87
- backnotprop/pstack★ 3.8ksame name
- langchain-ai/langchain-skills★ 1.3ksame name
- moeru-ai/xsai★ 667same name
- zaxbysauce/opencode-swarm★ 519same name
- ZaxbyHub/opencode-swarm★ 518same name
- guaardvark/guaardvark★ 306same name
- iha2/superlite★ 249same name
- apple-ouyang/book-to-skill★ 148same name
- jtaroreh/agystack★ 128same name
- uzairansaruzi/p3-stack★ 126same name
77 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository58 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- best-practices-auditSkill
- catalog-authoringSkill
- cli-toolsSkill
- conventional-commitsSkill
- councilSkill
- decompose-planSkill
- falsify-firstSkill
- find-skillsSkill
- harness-clientSkill
- harness-loopSkill
- hill-climbSkill
- interface-factsSkill
- no-commentsSkill
- nodeSkill
- plain-englishSkill
- pythonSkill
- release-processSkill
- repair-in-placeSkill
- retention-probeSkill
- root-causeSkill
- session-finishSkill
- skill-creatorSkill
- test-disciplineSkill
- tier-injectionSkill
- validate-as-consumerSkill
- work-trackerSkill
- worktree-isolationSkill
- best-practices-auditSkill
- catalog-authoringSkill
- cli-toolsSkill
- conventional-commitsSkill
- councilSkill
- decompose-planSkill
- falsify-firstSkill
- find-skillsSkill
- harness-clientSkill
- harness-loopSkill
- hill-climbSkill
- interface-factsSkill
- no-commentsSkill
- nodeSkill
- plain-englishSkill
- pythonSkill
- release-processSkill
- repair-in-placeSkill
- retention-probeSkill
- root-causeSkill
- session-finishSkill
- skill-creatorSkill
- swarmSkill
- test-disciplineSkill
- tier-injectionSkill
- validate-as-consumerSkill
- work-trackerSkill
- worktree-isolationSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 83 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 9
Run fresh agents on one artifact, one lens each.
- Distinctive: line 19
Launch: Start all agents in one message so they run in parallel, with the agent that lenses names for each lens.
- Distinctive: line 42
Ask the user before more than 8 agents at once.
“Common” is measured: kept by at least 6 in 10 of the 83 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.
Files
<!-- Generated by `basicly skills-build` from skill.yaml. Do not edit; edit the source. -->Swarm
Run fresh agents on one artifact, one lens each. Merge only what they prove. council and hill-climb reuse these steps by name.
The script is ${CLAUDE_SKILL_DIR}/scripts/swarm.py, in the folder of this SKILL.md. DIR is a new folder per run in the session scratchpad, such as swarm-merge-review-1.
Teardown mode is for "tear down", "rip apart" or "find everything wrong". It runs steps 1 to 7, then Answer and Fix.
Steps
- Frame. Name the artifact, the question and 3 to 6 lenses that do not overlap, with rubrics from lenses. In teardown mode the question is "what is wrong with this artifact?" and the lenses are the preset for its type. When the user names fewer than 3 lenses, add the closest lenses to reach 3 and say which. For one claim, propose
falsify-first, run by a fresh agent that did not make the claim; run the swarm when the user still asks for it. - Brief. Fill the brief once per lens: its rubric, a reading list of at most 6 items, a word cap of 400 unless the user sets one. Pass the artifact, never your own conclusion.
- Launch. Start all agents in one message so they run in parallel, with the agent that lenses names for each lens. Use lower effort for a mechanical lens.
- Collect. Save each reply as
DIR/LENS.md. Wait for each agent's completion notice; never write a reply for an agent that has not returned. An agent that fails or stops without a reply has not returned. Check. Run:
python3 -B ${CLAUDE_SKILL_DIR}/scripts/swarm.py check --lenses a,b,c --dir DIRExit 1 names each lens that is not run or malformed. Rerun that lens once with the same brief into the same
DIR, then run the check again. If it still fails, report it as not run.- Verify. Give each important finding to one more fresh agent. It confirms or refutes the finding with evidence, and runs
falsify-firstwhen the finding rests on a number, a root cause or an absence claim. Drop a refuted finding; mark a confirmed one verified, and any other one unverified. An absence finding stays unverified until the fresh agent's positive control, a known match run through the same search, passes. - Report. Give the user the script table, the verified important findings and numbered decisions with one recommendation each. Mark every finding that Verify did not verify as unverified, and every finding the script marks UNCITED as uncited. Name the agent that verified each claim.
Teardown mode: answer and fix
- Answer. Fill the responses table for every finding, each with its evidence. For each contested important finding, start one fresh agent with the finding and the counter-evidence; its answer stands.
- Fix. Fix every finding marked fixed and run the check that proves it. Ask before editing a file the user wrote or a file outside the repository. After 3 teardowns of one artifact, report what is still open; use
hill-climbwhen the goal is a higher grade.
Rules
- Each agent is fresh: it sees the artifact, its brief and its reading list, never another agent's reply.
- A missing report is "not run", never a pass.
- The author of the artifact never verifies or refutes a finding. When the user wants to verify findings themselves, name this rule, still run the fresh agent, and list the user's answers beside it.
- An important finding is fixed, contested or escalated. Decline one only when the user says so, marked "declined by the user", and name the rule the user overrode.
- Ask the user before more than 8 agents at once.
Read when needed
- Report format for the json block and the merge rules.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- 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.

