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magimagi 命令行

Agent Skill

magi 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,022

周安装

43

GitHub Stars

113

下载量

358
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:magi(magi 命令行)
来源仓库:https://github.com/vinta/hal-9000
仓库路径:skills/magi
安装命令:
npx skills add https://github.com/vinta/hal-9000 --skill magi
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/vinta/hal-9000 --skill magi

简介

magi 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合围绕仓库状态、代码变更或协作事项进行整理和使用。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需指定技能名称和仓库地址。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网或文件读写操作。
  • magi 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

MAGI

Multi-model brainstorming panel. Three teammates explore a question in parallel, each backed by a different model family, then the lead consolidates their proposals for the user.

  • Scientist: reasons directly as Claude Opus (no external dispatch)
  • Mother: delegates to OpenAI Codex via mcp__codex__codex MCP tool
  • Woman: delegates to Google Gemini via gemini CLI

Process

1. Clarify

If the question is underspecified, use AskUserQuestion to nail down purpose, constraints, and success criteria. Skip if already clear and actionable.

  • Ask questions one at a time to refine the idea
  • Prefer multiple choice questions when possible, but open-ended is fine too
  • Only one question per message

2. Setup

Read the personality and reference files, then spawn all teammates in parallel.

Files to read:

Create team with TeamCreate using name magi-{topic} (e.g., magi-auth-strategy).

Spawn all 3 teammates in a single message (3 parallel Agent calls with team_name set):

Teammatenamesubagent_typePrompt includes
Scientistscientistgeneral-purposeMAGI-1.md personality + question (reasons directly as Opus)
Mothermothergeneral-purposeMAGI-2.md personality + codex.md (dispatches to Codex MCP) + question
Womanwomangeneral-purposeMAGI-3.md personality + gemini.md (dispatches to Gemini CLI) + question

Include all clarified context in each spawn prompt: teammates have no conversation history.

3. Parallel Exploration

The lead's role is coordination only:

  • Wait for teammates to send proposals via SendMessage
  • Forward any teammate clarifying questions to the user via AskUserQuestion, noting which teammate (and model) asked. Never answer on the user's behalf: only the user answers.

4. Consolidate + Present

Collect all proposals, then:

  1. Deduplicate similar proposals (attribute to all teammates/models that proposed it)
  2. Group by theme if many proposals
  3. Present each option with:

- Which teammate(s) and model(s) proposed it (e.g., "Scientist [Opus]", "Mother [Codex]") - Trade-off analysis from each perspective - Who tagged it as their top pick and why

  1. Ask the user to select an option via AskUserQuestion
  2. Ask via AskUserQuestion what to do next:

- Write a plan: teardown, then handoff to writing-plans - Debate: another round of critique (see below) - Done: teardown, no further action

5. Debate (optional, user-triggered)

Only runs if the user requests it. Can be repeated.

  1. Broadcast the consolidated option list to all 3 teammates via SendMessage
  2. Each teammate critiques the proposals through their model (Scientist reasons directly; Mother and Woman follow Debate Mode in their reference files)
  3. Collect updated stances and re-present to the user (back to step 4)

6. Teardown

Tear down only when the user selects Write a plan or Done.

  1. shutdown_request to each teammate
  2. Wait for all shutdown approvals
  3. TeamDelete

7. Handoff (write a plan path only)

After teardown, invoke writing-plans skill with the chosen option(s) as context.

Gotchas

  • Teammates have no conversation history. Everything they need must be in the spawn prompt — the user's question, clarified context, CLAUDE.md, and their personality/reference files. If you forget context from the Clarify step, the teammate works blind.
  • TeamDelete fails if teammates are still active. Always send shutdown_request to all three and wait for approvals before calling TeamDelete.
  • Save the Codex threadId. Mother's first mcp__codex__codex call returns a threadId needed for debate follow-ups via mcp__codex__codex-reply. If lost, the debate round must re-send full context.
  • Gemini has no persistent thread. Unlike Codex, each Gemini call is stateless. For debate rounds, the full proposal list and persona must be re-sent every time.
  • Teammates may not report back. If a teammate goes silent, send a SendMessage nudge. After 2 minutes of silence, collect what you have and present partial results.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.01%
按下载量换算118

Claude

26.92%
按下载量换算96

Cursor

20.49%
按下载量换算73

Gemini CLI

10.12%
按下载量换算36

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/vinta/hal-9000 --skill magi 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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