decision-tree-builder

# 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", "type": "chance", "outcomes": [ {"name": "Market Grows", "probability": 0.5, "payoff": 600000}, {"name": "...