council
Skill0 starsChanged 10 days agoMITView on GitHub
Trigger this if the user says 'council' or 'arena'.
143 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- Beskars-Code/Skillstheir own version, first seen Nov 8, 2026
- Gabriel-Lafrance/Skillstheir own version, first seen Nov 8, 2026
- ong6/skillstheir own version, first seen Nov 8, 2026
- lbussell/agent-skillsedited, first seen Nov 8, 2026
- scottwater/skillstheir own version, first seen Nov 8, 2026
- T0mSIlver/skillsedited, first seen Nov 8, 2026
Used with
Projects with it also use agent-payment-x402, motion-advanced and 6 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.
TironFoxSkillagent-payment-x402
Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.
Also in 5 projects that use this
renepfSkillmotion-advanced
Advanced motion patterns for React / Next.js — drag & drop, gestures, text animations, SVG path drawing, custom hooks, imperative sequences (useAnimate), loaders, and the full API decision tree. Requires motion-foundations.
Also in 4 projects that use this
RojiosSkilldefi-amm-security
Security checklist for Solidity AMM contracts, liquidity pools, and swap flows. Covers reentrancy, CEI ordering, donation or inflation attacks, oracle manipulation, slippage, admin controls, and integer math.
Also in 6 projects that use this
RojiosSkilldart-flutter-patterns
Production-ready Dart and Flutter patterns covering null safety, immutable state, async composition, widget architecture, popular state management frameworks (BLoC, Riverpod, Provider), GoRouter navigation, Dio networking, Freezed code generation, and clean architecture.
Also in 5 projects that use this
TironFoxSkillopenclaw-persona-forge
为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡, 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill,可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于:微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词:龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。
Also in 4 projects that use this
ronmkrSkillvite-patterns
Vite build tool patterns including config, plugins, HMR, env variables, proxy setup, SSR, library mode, dependency pre-bundling, and build optimization. Activate when working with vite.config.ts, Vite plugins, or Vite-based projects.
Also in 5 projects that use this
- +1 more from Rojios
Other versions143 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- t3dotgg/tstack★ 2.5k61% same
- christofferbergj/agent-skills★ 132% same
- T0mSIlver/skills★ 161% same
- lbussell/agent-skills★ 057% same
- shubrt/skills★ 070% same
Wrote their own version · 138
- simstudioai/sim★ 30ksame name
- 0xNyk/council-of-high-intelligence★ 4.8ksame name
- danieleteti/delphimvcframework★ 1.4ksame name
- warpdotdev/common-skills★ 630same name
- QuixiAI/agi-memory★ 623same name
- QuixiAI/Hexis★ 623same name
- zaxbysauce/opencode-swarm★ 519same name
- ZaxbyHub/opencode-swarm★ 518same name
- boshu2/agentops★ 453same name
- automagik-dev/genie★ 351same name
128 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 repository24 other files it gives its agents.
- AGENTS.mdAGENTS.md
- rules/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- babysit-prSkill
- beast-uiSkill
- cleanupSkill
- doc-viewSkill
- featuremapSkill
- file-prSkill
- frontend-designSkill
- full-sendSkill
- full-stopSkill
- impeccableSkill
- leaving-pr-commentsSkill
- modernizeSkill
- no-commentsSkill
- patrolSkill
- sol-loopSkill
- statechartSkill
- technical-writingSkill
- tldrSkill
- untangleSkill
- verify-prSkill
- whySkill
The file
We split this skill into the rules it gives an agent
11 rules. 0 are common, 10 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 128 edited versions we read keep these.
10
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
- Distinctive: line 43
If the work ends in a pull request, put the results in the PR description.
- Distinctive: line 44
Put this section before the model and harness line at the end:
- Very specific: line 57
If a delegate gives no score, write no score.
- Distinctive: line 58
If the PR is open, edit the description.
- Distinctive: line 59
If there is no PR, put the same results in the final reply only.
- Distinctive: line 61
If you agree with their recommendations, make the changes and request a fresh review after.
- Distinctive: line 67
Do not let repeated reviews result in scope creep.
- Distinctive: line 72
Use this mode when the user asks the council to design, plan or choose an approach, or says "arena".
- Distinctive: line 75
Write the task and 3 to 6 criteria that a good plan meets.
- Distinctive: line 79
Start one judge from a model family other than yours.
- Distinctive: line 83
Read each plan in full and score it yourself.
“Common” is measured: kept by at least 6 in 10 of the 128 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
Council
Bring in delegates to help with the user's request, usually for review or feedback. By default, use Claude Opus and GPT Sol, in their latest versions, one seat each, at high reasoning effort. Start a delegate for each seat, also for the model that you run on. If the user names members, use only those, one seat each. If the user asks for more seats than members, fill the extra seats with copies, in the order of the user's list. Report a named member that you cannot reach. If you can reach only one model family, report it. Do not substitute a model.
In T3 Code, use orchestrator_capabilities to resolve the models, then
delegate_task to start one delegate per seat in parallel. Elsewhere, use
the harness's subagent tools when they can run the model. Otherwise start each
delegate as a background command with a CLI that runs the model. Set <effort> to high, unless the
user names another effort:
| CLI | Read-only command |
| Claude Code | claude -p --model <id> --effort <effort> --permission-mode plan (brief on stdin) |
| Codex | codex exec --sandbox read-only --model <id> -c model_reasoning_effort=<effort> - (brief on stdin) |
| Copilot CLI | copilot -p "<brief>" -s --model <id> --effort=<effort> --allow-tool 'read,shell(git diff:*),shell(git status:*),shell(git log:*),shell(git show:*)' |
| OpenCode | opencode run --agent plan --model <provider>/<id> --variant <effort> "<brief>" |
| Kiro CLI | kiro-cli chat --no-interactive --agent <name> --effort <effort> "<brief>", with the model in the agent file |
Copilot CLI and OpenCode can run models from several model families. Before
you decide that a family is out of reach, check which of these CLIs are on the
PATH.
Give each delegate the request and relevant context. For review or feedback, keep their work read-only. Collect their responses and summarize the useful findings, disagreements, and recommended next steps.
For a code review, ask each delegate for a score out of 10. Count each full review pass as one round. A fresh review after fixes starts a new round.
If the work ends in a pull request, put the results in the PR description. Put this section before the model and harness line at the end:
## Council review
Rounds: 2
| Delegate | Round 1 | Round 2 |
| --- | --- | --- |
| Claude Opus | 7/10 | 9/10 |
| GPT Sol | 8/10 | 10/10 |If a delegate gives no score, write no score. Do not invent one.
If the PR is open, edit the description. Do not post a comment for this.
If there is no PR, put the same results in the final reply only.
If you agree with their recommendations, make the changes and request a fresh review after. Continue this process until all delegates are satisfied with the outcome, for at most 3 rounds. The user can set another limit in the request or in their instructions. When the limit ends, report the open findings and let the user decide.
Do not let repeated reviews result in scope creep. It is your job to fight to keep scope limited.
Design mode
Use this mode when the user asks the council to design, plan or choose an approach, or says "arena".
- Write the task and 3 to 6 criteria that a good plan meets. Give each delegate the task, not the criteria.
- Each delegate writes its own plan, read-only. Delegates do not see the other plans.
- Start one judge from a model family other than yours. Give it the criteria and the plans, with labels such as "Plan A" and no model names. It scores each plan against each criterion. If the user named the members and none of them is from another family, do not start a judge, and say so.
- Read each plan in full and score it yourself. If you and the judge pick different plans, read both reasons before you decide.
- Take the best plan as the base. Add the strong parts of the other plans to it, and give the source of each part.
- Show the criteria, the scores, the plan that you took as the base, the merged plan with the source of each part, and the parts that you rejected. Build it only when the user asks.
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.

