A professional analytical toolkit providing classic decision-making models like SWOT and Decision Trees to help users navigate complex choices logically.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install decision-framework
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install decision-framework using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Decision Framework Skill?
The Decision Framework is a powerful asset within the Openclaw Skills ecosystem designed to eliminate indecision and cognitive bias. By providing five industry-standard structural models—SWOT analysis, the 10-10-10 rule, Decision Trees, Weighted Scoring, and the Eisenhower Matrix—it transforms vague dilemmas into actionable, data-driven insights. This skill acts as a rational partner, helping developers and managers evaluate risks, quantify options, and visualize long-term outcomes without overriding human agency.
Whether you are facing a career pivot, a technical architecture choice, or daily task prioritization, this tool guides you through a structured inquiry process. It ensures that internal strengths, external threats, and quantitative probabilities are all accounted for, delivering a professional-grade analysis in a clear markdown format.
Decision Framework Skill Use Cases
- Evaluating career transitions or business startup ideas using comprehensive strategic analysis.
- Resolving emotional or impulsive dilemmas by applying long-term perspective filters.
- Comparing multiple technical solutions or job offers through quantitative weighted scoring.
- Assessing financial investments or project risks using expected value calculations in decision trees.
- Managing overwhelming workloads by categorizing tasks into urgency and importance quadrants.
How Decision Framework Skill Works
- The agent identifies a decision-making trigger word such as SWOT, weighted scoring, or general expressions of indecision.
- It initiates a discovery phase to understand the core dilemma, available options, and the user's primary concerns (cost, time, risk).
- Based on the scenario, it recommends the most suitable Openclaw Skills framework or allows the user to select their preferred model.
- The agent guides the user through data collection, asking specific questions relevant to the chosen framework (e.g., asking for weights and scores for the Weighted Scoring model).
- It generates a structured output featuring tables, tree diagrams, or quadrant lists, providing key insights and a suggested direction while leaving the final choice to the user.
Decision Framework Skill Setup
To integrate this framework into your local environment, ensure you have the necessary scripts and reference guides from the Openclaw Skills repository.
# Navigate to your skills directory
cd openclaw-assets/skills
# Ensure the scoring script is executable
chmod +x scripts/weighted-scoring.py
# Access reference guides for advanced templates
cat references/decision-tree-guide.md
Decision Framework Skill Data Schema & Taxonomy
The skill organizes analysis into structured Markdown formats to ensure portability and clarity. Data is categorized as follows:
| Data Type | Format | Content Description |
|---|---|---|
| Strategic Analysis | Quadrant Lists | Internal (S/W) and External (O/T) factors for SWOT. |
| Quantitative Comparison | Markdown Tables | Dimensions, weights, and normalized scores for options. |
| Probabilistic Models | Tree Diagrams | Visual branching of choices, probabilities, and expected values. |
| Temporal Analysis | Bullet Points | Consequences across 10 minutes, 10 months, and 10 years. |
| Task Taxonomy | Matrix | Allocation of tasks into the four Eisenhower quadrants. |
Decision Framework Skill Advanced Features
- Multi-framework synthesis: Combine SWOT and Decision Trees for high-stakes strategic investments.
- Automated Scoring: Integration with Python scripts for precise calculation of weighted averages in complex procurement scenarios.
- Exportable Records: All analysis can be exported as standalone Markdown files for project documentation or future reference.
- Expected Value Calculation: Built-in logic for risk-adjusted financial forecasting within decision branches.
SKILL.md
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