agent-roster
Skill0 starsChanged 3 months agoMITView on GitHub
Coordinate a user-named roster of models or agents toward a higher-quality consensus without premature convergence. Use when several LLMs should solve, create, review, improve, diagnose, plan, recommend, design, or decide together.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- wjgoarxiv/litopencodetheir own version, first seen Oct 13, 2026
- Meuwtex/agent-rostertheir own version, first seen Oct 11, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- Meuwtex/agent-roster★ 2same name
- wjgoarxiv/litopencode★ 2same name
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.
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
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 11
Run a named roster through independent first positions, evidence-based deliberation, explicit objection resolution, and a late consensus …
- Distinctive: line 15
Prefer a short form:
- Distinctive: line 44
Run available tests, source checks, or held-out review.
- Distinctive: line 46
Before cross-examination, agents may share scores, failing tests, counterexamples, verified sources, interface contracts, and blockers.
≈ “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
Agent Roster
Run a named roster through independent first positions, evidence-based deliberation, explicit objection resolution, and a late consensus check.
Parse the request
Prefer a short form:
<model>, <model>, ... | <task>Examples:
sol, terra, luna | decide: should we adopt this architecture?
opus x2, sonnet | improve: proposal.mdNatural-language rosters work too. Optional controls can follow the task: judge=..., lead=..., consensus=..., or budget=....
Preserve requested model order and repeated seats. Resolve names against the harness's actual model controls. Never silently substitute, omit, or add a requested model. If the harness cannot honor the roster, report the limitation before running. If the user gives no roster, choose three meaningfully different available models or variants and announce them.
Set the consensus rule
Honor an explicit rule such as unanimity, supermajority, judge decision, or verifier threshold. Otherwise use qualified consensus: every seat must return accept or accept-with-caveat, and no unresolved objection may identify a material factual, logical, safety, or verification failure. A material objection must identify the affected issue, explain its likely effect, offer checkable support, and state a resolution path. If that bar is not met, report no consensus rather than manufacturing one.
Run the roster
- Lock a shared brief: objective, inputs, constraints, deliverable, evaluation rubric, consensus rule, and comparable per-seat budget.
- Give each seat the brief without peer positions. Collect its proposed answer or artifact, evidence, assumptions, confidence, and likely failure modes.
- Build a comparison matrix of distinct claims, agreements, conflicts, evidence, and unknowns. Do not treat vote count as proof.
- Cross-examine the disagreements. Send agents the conflicting claims and evidence, not persuasive peer transcripts. Ask for counterexamples, falsifying tests, missing evidence, or concrete repairs.
- Have every seat revise independently and state what changed its view, what remains unresolved, and its current confidence.
- Draft the consensus result only after that revision. Circulate it late for
accept,accept-with-caveat, orreject, each with a specific reason. - Run available tests, source checks, or held-out review. Verifiable failures override votes. Preserve dissent and stop at no consensus when a material objection survives.
Before cross-examination, agents may share scores, failing tests, counterexamples, verified sources, interface contracts, and blockers. Do not broadcast complete peer solutions or persuasive summaries. The lead routes communication; avoid unstructured all-to-all debate.
Route by task
- For the full consensus contract, message schema, and shared-workspace rules, read references/protocol.md.
- For new or existing research articles, read references/research-writing.md.
- To explain or modify the design, read references/interaction-tax.md.
Report
State the requested and resolved roster, consensus rule, comparison, decisive evidence, objections and their disposition, final verification status, and any minority report.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
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.

