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decision-advisor决策顾问

Agent Skill

decision-advisor 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

3,326

周安装

140

GitHub Stars

公开资料未说明

下载量

1,165
OpenClaw

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

MIT-0

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:decision-advisor(决策顾问)
来源仓库:https://github.com/banxian87/decision-advisor
安装命令:
openclaw skills install decision-advisor
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install decision-advisor

简介

用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率任务时使用。

  • 适用于探索选项、分析权衡和数据驱动建议场景。
  • 使用思想树方法提供支持。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 安装前需确认权限范围和维护状态。
  • decision-advisor 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
decision-advisor
description
Decision-making advisor using Tree of Thoughts for exploring options, analyzing trade-offs, and providing data-driven recommendations.

Decision Advisor

AI-powered decision advisor that uses Tree of Thoughts to explore multiple options, analyze trade-offs, and provide structured recommendations for complex decisions.


Use Cases

🎯 Technical Decisions

  • Technology stack selection
  • Architecture patterns
  • Build vs buy decisions
  • Tool evaluation

💼 Business Decisions

  • Product feature prioritization
  • Investment analysis
  • Strategic planning
  • Risk assessment

👥 Personal Decisions

  • Career choices
  • Education paths
  • Major purchases

Features

🌳 Option Exploration

  • Generate multiple alternatives
  • Consider non-obvious options
  • Explore different perspectives

⚖️ Trade-off Analysis

  • Pros and cons for each option
  • Risk assessment
  • Cost-benefit analysis
  • Long-term implications

📊 Structured Framework

  • Decision criteria definition
  • Weighted scoring
  • Sensitivity analysis
  • Recommendation with confidence level

Usage

const advisor = new DecisionAdvisor();

const decision = await advisor.advise({
  decision: 'Choose frontend framework for enterprise app',
  options: ['React', 'Vue', 'Angular'],
  criteria: [
    { name: 'Performance', weight: 0.3 },
    { name: 'Developer Experience', weight: 0.25 },
    { name: 'Ecosystem', weight: 0.25 },
    { name: 'Long-term Support', weight: 0.2 }
  ],
  context: 'Team of 20 developers, 5-year project lifespan'
});

console.log(decision.recommendation);
console.log(decision.analysis);

Example Output

## Decision Analysis: Frontend Framework Selection

### Options Evaluated
1. React
2. Vue
3. Angular

### Scoring Matrix

| Criteria              | Weight | React | Vue | Angular |
|-----------------------|--------|-------|-----|---------|
| Performance           | 30%    | 8.5   | 8.0 | 7.5     |
| Developer Experience  | 25%    | 9.0   | 8.5 | 7.0     |
| Ecosystem             | 25%    | 9.5   | 7.5 | 8.5     |
| Long-term Support     | 20%    | 9.0   | 7.0 | 9.0     |
| **Weighted Score**    |        | **8.95** | 7.85 | 7.95 |

### Recommendation

**React** is recommended with a weighted score of 8.95/10.

### Key Reasons
1. Largest ecosystem and community
2. Excellent developer experience
3. Strong corporate backing (Meta)
4. Proven at scale

### Risks & Mitigations
- **Risk**: Frequent breaking changes
- **Mitigation**: Use stable LTS versions, invest in testing

### Confidence Level: High (85%)

Architecture

Decision Request
    ↓
Tree of Thoughts Agent
    ├─ Generate options
    ├─ Explore variations
    └─ Identify criteria
    ↓
Evaluation Phase
    ├─ Score each option
    ├─ Analyze trade-offs
    └─ Assess risks
    ↓
Recommendation Engine
    ├─ Weighted scoring
    ├─ Sensitivity analysis
    └─ Confidence calculation
    ↓
Structured Report

Installation

clawhub install decision-advisor

License

MIT


Version

1.0.0


Created

2026-04-02

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

98.16%
按下载量换算1,144

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

权限需确认

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安装前确认

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来源信息

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