Decision Expert

A decision support skill that helps users analyze options, weigh trade-offs, and apply decision frameworks (SWOT, decision matrix, pros/cons, etc.) across va...

Security Scan

The skill's code, CLI, and instructions are consistent with a local decision-support tool and do not request unrelated credentials, network endpoints, or system-wide privileges.

Purpose & Capability

The name/description (decision frameworks, matrix, SWOT, pros/cons) directly match the included CLI (cli.js), core library (lib/index.js), README, and SKILL.md examples. Required env vars, binaries, and config paths are none, which is proportionate for a local analysis tool.

Instruction Scope

SKILL.md instructs using the provided CLI and its commands (analyze, pros-cons, swot, matrix, etc.). The runtime instructions and CLI code operate on user-supplied inputs and local output files; they do not instruct reading unrelated system files, accessing secrets, or sending data to external endpoints.

Install Mechanism

There is no install spec in the registry metadata (instruction-only), but the package includes normal Node.js project files and a bin entry for a CLI. Dependencies are common (commander, chalk, inquirer, etc.). No downloads from ad-hoc URLs or extracted archives are present.

Credentials

The skill requests no environment variables, no credentials, and no config paths. The code does not reference environment secrets or external API tokens, which is appropriate for an offline/local decision-analysis tool.

Persistence & Privilege

Flags are default (always:false) and the skill does not request permanent agent presence or modify other skills. The code persists decision objects only in-memory and can export to files when the user requests output; there is no built-in background service or automatic exfiltration.

Assessment

This skill appears coherent and self-contained: it implements local decision frameworks and a CLI without requiring credentials or network access. Before installing, you may want to (1) verify the package source/repository URL matches a trusted origin (the registry lists a GitHub URL and homepage but the skill source was noted as 'unknown'), (2) inspect package.json and run npm install / npm audit locally, (3) run the CLI in an isolated environment (or review the code) if you are cautious, and (4) be aware that using --output will write files you specify. If you need guarantees about provenance, confirm the upstream repo and signatures before trusting long-term use.

Decision Expert Skill

A comprehensive decision support system that helps users make better choices by providing structured analysis, decision frameworks, and objective evaluation of options.

When to Use This Skill

Use this skill when the user:

• Asks for help making a decision (e.g., "Should I buy X or Y?", "Which job should I take?", "Is this investment good?")
• Wants to weigh pros and cons of different options
• Needs a structured framework to evaluate choices
• Is facing a complex decision with multiple factors
• Wants to document and track their decision-making process
• Needs to compare alternatives systematically

Common trigger phrases:

• "帮我决定..." (help me decide...)
• "哪个更好？" (which is better?)
• "应该选哪个？" (which should I choose?)
• "买什么手机？" (what phone should I buy?)
• "该不该换工作？" (should I change jobs?)
• "投资这个项目好吗？" (is this investment good?)

Command Design

The skill provides a CLI command decision with the following structure:

Basic Commands

# Get help and list available frameworks
decision help

# Analyze a decision with automatic framework selection
decision analyze "买什么手机" --options "iPhone 15, Samsung Galaxy S24, Google Pixel 8"

# Create a pros/cons list
decision pros-cons "换工作到上海" --pros "高薪, 发展机会" --cons "高房价, 离家远"

# Use a specific decision framework
decision swot "开咖啡店" --strengths "热爱咖啡, 有经验" --weaknesses "资金有限" --opportunities "社区需求" --threats "竞争激烈"

# Create a decision matrix
decision matrix "买车" --criteria "价格, 油耗, 安全性, 空间" --options "SUV, 轿车, 电动车" --weights "30, 20, 25, 25"

# Compare multiple options
decision compare "度假地点" --options "巴厘岛, 日本, 欧洲" --factors "预算, 时间, 兴趣, 便利性"

Interactive Mode

# Start an interactive decision-making session
decision interactive

# Guided decision workflow
decision guide "职业选择"

Scenario-Specific Commands

# Shopping decisions
decision shopping "笔记本电脑" --budget 8000 --needs "编程, 设计, 便携"

# Career decisions  
decision career "offer选择" --offers "公司A: 高薪但忙, 公司B: 平衡但薪低"

# Investment decisions
decision investment "买房 vs 租房" --timeframe "5年" --risk "中等"

# Daily life decisions
decision daily "早上锻炼还是晚上锻炼" --factors "精力水平, 时间安排, 坚持难度"

Output Formats

# Export decision analysis to different formats
decision analyze "买手机" --format markdown --output decision.md
decision analyze "买手机" --format json --output decision.json
decision analyze "买手机" --format table --display

Decision Frameworks Design

The skill implements several proven decision-making frameworks:

1. Pros & Cons List (利弊分析)

• Simple listing of advantages and disadvantages
• Weighted scoring option
• Visual balance display

2. SWOT Analysis (SWOT分析)

• Strengths, Weaknesses, Opportunities, Threats
• Internal vs. external factors
• Strategic implications

3. Decision Matrix (决策矩阵)

• Multiple criteria with weights
• Option scoring (1-5 or 1-10 scale)
• Weighted total calculation
• Sensitivity analysis

4. Cost-Benefit Analysis (成本效益分析)

• Quantitative evaluation of costs vs. benefits
• ROI calculation
• Time value of money consideration

5. Decision Tree (决策树)

• Branching scenarios with probabilities
• Expected value calculation
• Risk assessment

6. Eisenhower Matrix (艾森豪威尔矩阵)

• Urgent vs. important classification
• Priority setting
• Time management decisions

7. Weighted Scoring Model (加权评分模型)

• Custom criteria with importance weights
• Objective scoring rubrics
• Comparative analysis

8. Six Thinking Hats (六顶思考帽)

• Parallel thinking framework
• Multiple perspective consideration
• Emotionally intelligent decision making

9. Pareto Analysis (帕累托分析)

• 80/20 principle application
• Focus on high-impact factors
• Resource allocation decisions

10. Scenario Planning (情景规划)

• Multiple future scenarios
• Contingency planning
• Robustness testing

Supported Decision Scenarios

Shopping & Purchases (购物决策)

• Electronics (phones, laptops, gadgets)
• Vehicles (cars, bikes)
• Real estate (buying, renting)
• Appliances and home goods
• Fashion and personal items
• Subscription services

Career & Education (职业与教育)

• Job offers and career moves
• Education paths and courses
• Skill development investments
• Business opportunities
• Freelance vs. employment
• Promotion decisions

Investment & Finance (投资与财务)

• Stock and investment choices
• Real estate investments
• Business investments
• Savings and retirement planning
• Loan and debt decisions
• Insurance choices

Daily Life & Personal (日常生活)

• Health and fitness choices
• Relationship decisions
• Time management
• Habit formation
• Travel planning
• Home improvement

Business & Strategy (商业与战略)

• Product development choices
• Market entry decisions
• Hiring and team building
• Vendor selection
• Technology adoption
• Strategic partnerships

Project & Technical (项目与技术)

• Technology stack selection
• Architecture decisions
• Tool and platform choices
• Implementation approaches
• Resource allocation
• Risk management

Technical Implementation Suggestions

Core Architecture

decision-expert/
├── cli/                    # Command-line interface
│   ├── index.js           # Main CLI entry point
│   ├── commands/          # Individual command implementations
│   └── utils/             # CLI utilities
├── lib/                   # Core decision logic
│   ├── frameworks/        # Decision framework implementations
│   ├── models/           # Data models (Decision, Option, Criterion, etc.)
│   ├── analysis/         # Analysis algorithms
│   └── visualization/    # Output formatting and display
├── scenarios/            # Scenario-specific logic
│   ├── shopping.js
│   ├── career.js
│   ├── investment.js
│   └── daily.js
├── storage/              # Decision history and templates
│   ├── history/
│   ├── templates/
│   └── exports/
└── interactive/          # Interactive session manager
    ├── prompts.js
    ├── workflows.js
    └── ui.js

Key Implementation Components

1. Decision Engine: Core logic for applying frameworks and calculating scores
2. Framework Library: Modular implementations of each decision framework
3. Scenario Adapters: Specialized logic for different decision domains
4. Interactive Shell: Guided workflow for complex decisions
5. Storage System: Save/load decisions, templates, and history
6. Export System: Multiple output formats (Markdown, JSON, HTML, CSV)

Dependencies

{
  "dependencies": {
    "commander": "^11.0.0",      // CLI framework
    "inquirer": "^9.2.0",        // Interactive prompts
    "chalk": "^5.3.0",           // Terminal styling
    "cli-table3": "^0.6.3",      // Table displays
    "lodash": "^4.17.21",        // Utility functions
    "yaml": "^2.3.0",            // YAML parsing for templates
    "json2csv": "^6.0.0",        // CSV export
    "markdown-table": "^3.0.3"   // Markdown table generation
  },
  "devDependencies": {
    "jest": "^29.7.0",           // Testing
    "eslint": "^8.50.0"          // Code quality
  }
}

API Design

// Core decision API
const decisionEngine = {
  createDecision(description, options, criteria),
  applyFramework(decision, framework, params),
  calculateScores(decision, weights),
  generateRecommendation(decision),
  exportDecision(decision, format)
};

// Framework implementations
const frameworks = {
  prosCons: { analyze(options, pros, cons) },
  swot: { analyze(strengths, weaknesses, opportunities, threats) },
  decisionMatrix: { analyze(options, criteria, weights, scores) },
  costBenefit: { analyze(costs, benefits, timeframe, discountRate) }
};

Interactive Features

1. Step-by-step guidance: Walk users through decision process
2. Template system: Pre-built decision templates for common scenarios
3. History tracking: Record and learn from past decisions
4. Collaboration support: Share decisions and get input from others
5. Reminder system: Follow up on decision outcomes
6. Learning system: Improve suggestions based on user preferences

File Structure Recommendations

Minimum Viable Structure

~/.openclaw/workspace/skills/decision-expert/
├── SKILL.md                      # This file
├── README.md                     # User documentation
├── package.json                  # Node.js package definition
├── cli.js                        # Main CLI entry point
├── lib/
│   ├── index.js                  # Main library export
│   ├── decision-engine.js        # Core decision logic
│   ├── frameworks/               # Framework implementations
│   │   ├── pros-cons.js
│   │   ├── swot.js
│   │   ├── decision-matrix.js
│   │   └── index.js
│   └── utils/
│       ├── formatters.js         # Output formatting
│       └── validators.js         # Input validation
├── templates/                    # Decision templates
│   ├── shopping/
│   ├── career/
│   └── investment/
├── examples/                     # Example usage
│   ├── phone-decision.md
│   ├── job-offer-decision.json
│   └── investment-analysis.csv
└── scripts/                      # Utility scripts
    ├── setup.sh                  # Installation script
    └── test-decision.sh          # Test script

Advanced Structure (Full Implementation)

~/.openclaw/workspace/skills/decision-expert/
├── .github/                      # GitHub workflows
│   └── workflows/
│       └── test.yml
├── bin/                          # Executable scripts
│   └── decision
├── src/                          # TypeScript source
│   ├── cli/
│   ├── lib/
│   ├── types/
│   └── utils/
├── tests/                        # Comprehensive test suite
│   ├── unit/
│   ├── integration/
│   └── fixtures/
├── docs/                         # Detailed documentation
│   ├── frameworks/
│   ├── scenarios/
│   └── api/
├── config/                       # Configuration files
│   ├── default-config.yaml
│   └── scenario-config.yaml
├── data/                         # Sample data and templates
│   ├── templates/
│   ├── examples/
│   └── benchmarks/
├── public/                       # Web assets (if any)
│   ├── css/
│   └── js/
└── dist/                         # Compiled output (for TypeScript)

Integration with OpenClaw

The decision assistant skill can integrate with OpenClaw in several ways:

1. Direct CLI usage: Users run decision commands directly
2. Agent integration: Pearl can call the decision assistant when users need help with decisions
3. API mode: Other skills can use the decision engine via JavaScript API
4. Template sharing: Decision templates can be shared across the OpenClaw ecosystem

Example Agent Integration

// Pearl agent can use the decision assistant like this:
const { analyzeDecision } = require('decision-expert');

async function helpWithDecision(userQuery, options) {
  const analysis = await analyzeDecision(userQuery, options);
  return `Based on my analysis: ${analysis.recommendation}\n\n${analysis.summary}`;
}

Getting Started

Quick Start

# Install the skill
npx skills add <owner/repo>@decision-expert

# Or install locally for development
cd ~/.openclaw/workspace/skills/decision-expert
npm install
npm link  # Makes 'decision' command available globally

# Test with a simple decision
decision help
decision analyze "晚饭吃什么" --options "中餐, 西餐, 日料"

Development Setup

# Clone and setup
git clone <repository> ~/.openclaw/workspace/skills/decision-expert
cd ~/.openclaw/workspace/skills/decision-expert
npm install

# Run tests
npm test

# Build (if TypeScript)
npm run build

# Run in development mode
node cli.js help

Learning Resources

• Decision Theory: Understanding rational choice models
• Behavioral Economics: Cognitive biases in decision making
• Operations Research: Quantitative decision analysis methods
• Psychology of Choice: How people actually make decisions
• Business Strategy: Strategic decision frameworks

Contributing

This skill welcomes contributions! Areas needing improvement:

1. Additional decision frameworks
2. More scenario-specific templates
3. Better visualization options
4. Integration with other tools (calendar, task managers, etc.)
5. Multi-language support
6. Accessibility improvements

License

[MIT License] - Open for use and modification within the OpenClaw ecosystem.

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"Good decisions come from experience, and experience comes from bad decisions." - This skill helps you get more experience without the bad decisions.