meeting-facilitate

meeting-facilitate is a skill for Claude Code from CronusL-1141/AI-company. It costs 72 tokens per session (4,456 once invoked), scanned A, original, MIT.

A process for running structured meetings between multiple software agents. It covers choosing a meeting format, bringing in participants, managing discussion rounds, checking attendance, and producing a summary.

In plain words
What is it for?
Use it for agent-based brainstorming, decision-making, code or delivery reviews, project retrospectives, daily status meetings, and resolving disagreements.
Why use it?
It prevents meetings from being created without participants, stops one agent from speaking for another, and checks that everyone has contributed before the meeting ends.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ai-team-os plugin — 5 skills, 8 commands, 25 agents, 15 hooks, 1 MCP server shipped together

Good fit Use it for agent-based brainstorming, decision-making, code or delivery reviews, project retrospectives, daily status meetings, and resolving disagreements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cronusl-1141/ai-company/meeting-facilitate
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add CronusL-1141/AI-company --skill meeting-facilitate
Clone the repo
git clone --depth 1 https://github.com/CronusL-1141/AI-company

Made for: Claude Code.

Or install ai-team-os, the plugin that ships this one along with the rest of its 5 skills, 8 commands, 25 agents, 15 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for meeting-facilitate

README.md
[![agentmods](https://agentmods.dev/badge/skills/cronusl-1141/ai-company/meeting-facilitate/github.svg)](https://agentmods.dev/skills/cronusl-1141/ai-company/meeting-facilitate)
Your own site
<a href="https://agentmods.dev/skills/cronusl-1141/ai-company/meeting-facilitate"><img src="https://agentmods.dev/badge/skills/cronusl-1141/ai-company/meeting-facilitate/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for meeting-facilitate

Your own site · 80×15
<a href="https://agentmods.dev/skills/cronusl-1141/ai-company/meeting-facilitate"><img src="https://agentmods.dev/badge/skills/cronusl-1141/ai-company/meeting-facilitate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,456 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.04456
Opus 5 $0.00036 $0.02228
Sonnet 5 $0.00014 $0.00891
Haiku 4.5 $0.00007 $0.00446

Measured 13d ago against content hash c8dc45c0599e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

meeting-facilitate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/skills/meeting-facilitate/SKILL.md · 357 lines

How it starts

The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Meeting Facilitate — 会议主持技能

本技能指导你(Leader 或具备主持职责的 Agent)端到端组织一场多 Agent 会议:选模板 → 创建会议 → spawn 真实参与者 → 签到 → 推进轮次 → 验证全员发言 → 结束并汇总。

前置要求

  • 知道自己的 agent_id(用于以主持人身份发言)——它由 SubagentStart 注入的「你的 OS 身份」块给出; 拿不到就 GET /api/agents/whoami?name=<你的名字>&session_id=<会话id> 自查(服务端按 cc id / 会话+名 反查)
  • 已明确:会议目的、需要的角色、目标产出
  • 已知会议涉及的关键文件路径(用于 materials/context_files)

核心原则(看完这三条再往下读)

  1. OS 不会自动 spawn 参与者meeting_create 只创建会议记录和 dispatch_plan,真正让参与者到场必须靠你亲自调用 Agent tool。光创建不 spawn = 没人到场 = 会议失败。
  2. 绝不代打他人发言 — 你以主持人身份发言时,agent_idcaller_agent_id 必须都填你自己的 ID。用别人的 agent_id 发言会被 OS 标记为 impersonation=true 并写入审计日志。
  3. conclude 前必须确认全员发言meeting_conclude 默认开启 validate_attendance,未发言者会让 conclude 返回 400。不要用 force=True 绕过——除非有不可抗力的技术理由。

主持流程(7 步)

Step 1: 选择会议模板

根据会议目的对照下表选模板。详细模板说明见 templates/<name>.md(progressive disclosure)。

目的 推荐模板 轮数 为何
发散创意、产生新想法 brainstorm 4 独立发散 → 交叉启发 → 评估 → 汇总
多方案中做选择 decision 3 陈述 → 质询 → 收敛
评审代码 / PR / 交付物 review 3 陈述 → 独立评审 → 回应裁定
项目复盘、提取教训 retrospective 3 4Ls → 改进方向 → 承诺计划
每日进度同步 standup 1 三问:完成 / 计划 / 阻塞
决策有重大分歧或风险 debate 4 正方陈述 → 反方质疑 → 正方回应 → 裁决
开放议程、自由议题 lean_coffee 3 议题收集 → 投票 → 时间盒讨论
架构 / 方案多视角评审 council 3 专家视角 → 交叉质询 → 裁决

不确定?用 template="free",OS 会根据 topic 关键词自动推荐。

Step 2: 创建会议(拿到 dispatch_plan)

必须使用结构化 participants(dict 列表),否则 dispatch_plan 里的 launch_call 会是空的,无法 ready-to-paste。

meeting_create(
    topic="评审 v0.9 Prompt Registry 架构方案",
    template="council",                           # Step 1 选的模板
    team_id="repo-insight-arch",                  # 可省略,自动用活跃团队
    team_name="repo-insight-arch",                # 仅 OS 侧归属;不会写进 launch_call
    participants=[
        {
            "name": "arch-lead",
            "agent_template": "software-architect",
            "role": "评估架构整体可行性与分层合理性",
            "context_files": ["docs/v0.9-prompt-registry.md"],
            "expected_output": "三段式:可行性 / 风险 / 建议",
        },
        {
            "name": "backend-arch",
            "agent_template": "backend-architect",
            "role": "评估存储层与 API 设计",
            "context_files": ["docs/v0.9-prompt-registry.md", "src/aiteam/storage/repository.py"],
            "expected_output": "存储方案 + 接口契约 + 迁移路径",
        },
    ],
    rounds=[                                       # 可选,省略则用模板默认 rounds
        {"topic": "立场陈述", "rule": "每人 3 段:评估视角 / 风险点 / 评分 1-5"},
    ],
    materials=["docs/v0.9-prompt-registry.md"],   # 全员必读
)

Read the full file on GitHub · 357 lines

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 357 lines · 72 tokens per session scan A c8dc45c0599e

Subscribe to this mod's changes

meeting-facilitate is a skill published in the GitHub repository CronusL-1141/AI-company (357 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 4,456 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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