decision-tree-builder
Automated decision tree construction skill for structuring complex decisions with probabilities, payoffs, and expected value calculations
npx skills add a5c-ai/babysitter --skill decision-tree-builder --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Decision Tree Builder ## Overview The Decision Tree Builder skill provides automated construction and analysis of decision trees for structuring complex business decisions. It enables systematic evaluation of alternatives through probability assignments, payoff calculations, and expected value analysis, supporting both prescriptive decision-making and sensitivity analysis. ## Capabilities - Decision node and chance node creation - Probability assignment and validation - Expected value calculation - Decision path optimization - Sensitivity analysis on probabilities - Rollback analysis automation - Decision tree visualization generation - Export to standard formats (JSON, XML) ## Used By Processes - Structured Decision Making Process - Multi-Criteria Decision Analysis (MCDA) - Decision Quality Assessment ## Usage ### Basic Decision Tree Construction ```python # Define decision structure decision_tree = { "type": "decision", "name": "Market Entry Strategy", "alternatives": [ { "name": "Enter Now", "type": "chance", "outcomes": [ {"name": "High Demand", "probability": 0.6, "payoff": 1000000}, {"name": "Low Demand", "probability": 0.4, "payoff": -200000} ] }, { "name": "Wait and See",
- Overview
- Capabilities
- Used By Processes
- Usage
- Basic Decision Tree Construction
- Expected Value Calculation
- Sensitivity Analysis
- Visualization Output
- Input Schema
- Output Schema
- Best Practices
- Integration Points
What does the decision-tree-builder skill do?
Automated decision tree construction skill for structuring complex decisions with probabilities, payoffs, and expected value calculations
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill decision-tree-builder --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.