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

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Interactive Mode

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Scenario-Specific Commands

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Output Formats

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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

CODEBLOCK4

Key Implementation Components

1. 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

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API Design

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Interactive Features

1. 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

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Advanced Structure (Full Implementation)

CODEBLOCK8

Integration with OpenClaw

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

1. 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

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Getting Started

Quick Start

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Development Setup

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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. 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.