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decisionsdecisions 命令行

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

196

周安装

8

GitHub Stars

37

下载量

63
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:decisions(decisions 命令行)
来源仓库:https://github.com/majesticlabs-dev/majestic-marketplace
仓库路径:skills/decisions
安装命令:
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill decisions
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 decisions

简介

用于辅助测试设计、自动化测试、用例整理和回归验证。

  • 适合编写单元测试、端到端测试、测试计划或根据失败日志定位问题。
  • 使用时需确认项目测试框架、运行命令和夹具数据。
  • 涉及浏览器或外部服务时应区分本地模拟、测试环境与生产环境。
  • decisions 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Business Decision Analysis

Audience: Founders and leaders facing significant business decisions.

Goal: Facilitate business decisions via Tree of Thoughts (ToT) with 4-expert panel debate.

Input Schema

challenge: string           # Business problem to evaluate
complexity: simple|complex  # Determines depth (inferred or asked)
constraints: string[]       # Optional: budget, timeline, resources

Expert Panel

ConsultantFocus Areas
Growth StrategistRevenue opportunities, market expansion, competitive advantage
Operations ExpertFeasibility, implementation complexity, resource requirements
Financial AnalystROI, cost structures, cash flow impact, risk-adjusted returns
Skeptic Risk AnalystFailure modes, worst-case scenarios, hidden risks, blind spots

Analysis Workflow

1. Challenge Assessment

Determine complexity:

  • Complex triggers: >$100K investment, >20% team impact, market entry/exit, M&A

2. Branch Generation

For each consultant (Growth, Operations, Financial):

  • Generate 3 distinct approaches
  • For each approach:

- Identify 2-3 potential outcomes with probability assessment - List pros and cons - Quantify impact where possible

3. Risk Analysis

Skeptic reviews all 9 approaches:

  • For each approach:

- Identify primary failure mode - Describe worst-case scenario - Expose hidden assumptions

  • List critical blind spots across all approaches

4. Consultant Debate

  • Identify points of agreement
  • Surface disagreements with reasoning from each position
  • Resolve conflicts with documented resolution rationale
  • Synthesize perspectives into coherent view

5. Recommendation

Produce:

  • Selected approach name
  • Why this wins over alternatives
  • 3-5 key success factors
  • 2-3 critical risks to monitor
  • Confidence level (High/Medium/Low) with explanation

6. Implementation Planning (Complex Only)

For each of 5 key milestones:

  • Evaluate 3 execution strategies
  • Identify dependencies and bottlenecks
  • Create contingency plan for primary failure mode

Output Schema

analysis:
  challenge: string
  phases:
    branch_generation:
      - consultant: string
        approaches:
          - name: string
            description: string
            outcomes:
              - description: string
                probability: string  # High/Medium/Low or percentage
            pros: string[]
            cons: string[]
    risk_analysis:
      approach_risks:
        - approach: string
          failure_mode: string
          worst_case: string
          hidden_assumption: string
      blind_spots: string[]
    debate:
      agreements: string[]
      disagreements:
        - topic: string
          positions: {consultant: position}[]
          resolution: string
      synthesis: string
    recommendation:
      approach: string
      reasoning: string
      success_factors: string[]
      risks_to_monitor: string[]
      confidence: High|Medium|Low
      confidence_rationale: string
  implementation:  # Only if complexity == complex
    milestones:
      - name: string
        strategies: string[]
        dependencies: string[]
        bottlenecks: string[]
        contingency: string

Error Handling

ConditionAction
Vague challengeAsk clarifying questions about scope, constraints, success criteria
Consultants reach same conclusionsPush for genuine disagreement; explore edge cases
No clear winner among approachesPresent top 2 with explicit trade-off comparison
Confidence is LowState what specific information would raise confidence
User wants quick answerOffer abbreviated single-consultant analysis with caveats

Constraints

  • Consultants must genuinely disagree, not rubber-stamp
  • Quantify impact, probability, timelines where possible
  • State uncertainty honestly
  • Recommendation must be executable, not theoretical

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

37.53%
按下载量换算24

Claude

29.53%
按下载量换算19

Cursor

17.85%
按下载量换算11

Gemini CLI

9.96%
按下载量换算6

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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