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devils-advocate魔鬼代言人

Agent Skill

devils-advocate 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

2,002

周安装

86

GitHub Stars

37

下载量

702
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:devils-advocate(魔鬼代言人)
来源仓库:https://github.com/majesticlabs-dev/majestic-marketplace
仓库路径:skills/devils-advocate
安装命令:
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill devils-advocate
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/majesticlabs-dev/majestic-marketplace --skill devils-advocate

简介

该技能实施预提交对抗性推理,防止过早锁定技术选型决策。

  • 适用于架构选型、框架对比等非单一最优解场景的盲点暴露。
  • 需在每次重大决策前激活,提出反方论点直至达成共识。
  • 跳过条件包括执行已确定方案或存在明显唯一正确路径时。
  • devils-advocate 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Devil's Advocate Protocol

Pre-commitment adversarial reasoning to prevent early lock-in and expose blind spots.

When to Apply

Activate this protocol when:

  • Choosing between architectural approaches
  • Selecting libraries, frameworks, or tools
  • Planning implementation strategy
  • Recommending one approach over alternatives
  • User asks "should I...", "what's the best way to...", "which approach..."
  • During architect, Plan, or blueprint workflows
  • Making trade-off decisions with non-obvious answers

When to Skip

Do NOT apply when:

  • Executing already-decided implementation
  • Single obvious path exists (no real alternatives)
  • User explicitly chose the approach ("use X to do Y")
  • Task is mechanical/procedural, not decisional
  • Trivial choices with negligible impact

The Protocol

Step 1: Identify the Commitment

Before recommending an approach, explicitly state:

  • What decision is being made
  • What approach you're inclined toward
  • Why you're drawn to it

Step 2: Steel-Man the Opposition

Present the strongest case AGAINST your inclination:

  • What could go wrong?
  • What are you assuming that might be false?
  • What would a smart critic say?
  • What's the opportunity cost?
  • Under what conditions would this fail?

Requirements:

  • Be genuinely adversarial, not token objections
  • Attack the strongest version of your argument
  • Include at least one non-obvious failure mode

Step 3: Defend or Pivot

After the adversarial pass:

  • Explain why the approach might still be correct despite objections
  • What conditions make this the right choice?
  • What would need to be true for alternatives to win?
  • OR: Acknowledge the objections changed your recommendation

Step 4: Present with Confidence Calibration

Final recommendation should include:

  • Clear recommendation with reasoning
  • Key assumptions that must hold
  • Conditions that would invalidate this choice
  • Monitoring signals to watch for

Output Format

## Decision: [What's being decided]

### Initial Inclination
[Approach] because [reasons]

### Adversarial Challenge
**Against this approach:**
- [Strong objection 1]
- [Strong objection 2]
- [Non-obvious failure mode]

**What I might be wrong about:**
- [Assumption that could be false]

### Resolution
[Why it's still correct OR why I'm changing recommendation]

### Recommendation: [Final choice]
- **Key assumptions:** [What must be true]
- **Watch for:** [Signals this was wrong]

Relationship to Other Tools

  • reasoning-verifier: Post-hoc verification of completed reasoning
  • devils-advocate: Pre-commitment challenge before reasoning solidifies
  • Use both: devils-advocate during planning, reasoning-verifier after execution

Underlying Principle

LLMs commit to answers early and rationalize backward. This protocol interrupts that pattern by forcing exploration of the solution space before commitment crystallizes.

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

31.66%
按下载量换算222

Claude

29.32%
按下载量换算206

Cursor

19.56%
按下载量换算137

Gemini CLI

10.04%
按下载量换算70

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。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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