Decision visualization

Skill a5c-ai/babysitter/library/specializations/domains/business/decision-intelligence/skills/decision-visualization

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npx -y skills add a5c-ai/babysitter --skill decision-visualization

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Decision-specific visualization skill for creating clear, actionable visual representations of analyses

SKILL.md

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Decision Visualization

Overview

The Decision Visualization skill provides specialized visualization capabilities for decision support, creating clear, actionable visual representations that communicate analysis results effectively to decision-makers and stakeholders.

Capabilities

Decision tree diagrams
Strategy tables and consequence matrices
Trade-off scatter plots
Value-of-information graphs
Confidence/uncertainty bands
Waterfall charts for sensitivity
Heat maps for MCDA
Interactive dashboards

Used By Processes

Executive Dashboard Development
Structured Decision Making Process
Multi-Criteria Decision Analysis (MCDA)
Decision Documentation and Learning

Usage

Decision Tree Visualization

# Decision tree diagram configuration
decision_tree_viz = {
    "type": "decision_tree",
    "data": decision_tree_structure,
    "options": {
        "node_shapes": {
            "decision": "square",
            "chance": "circle",
            "terminal": "triangle"
        },
        "show_probabilities": True,
        "show_payoffs": True,
        "highlight_optimal_path": True,
        "color_scheme": "sequential",
        "orientation": "horizontal"
    }
}

Strategy Table

# Strategy comparison table
strategy_table = {
    "type": "strategy_table",
    "alternatives": ["Strategy A", "Strategy B", "Strategy C"],
    "criteria": ["Cost", "Time", "Quality", "Risk"],
    "data": performance_matrix,
    "options": {
        "color_coding": "performance_based",
        "show_weights": True,
        "show_scores": True,
        "highlight_winner": True
    }
}

Trade-off Scatter Plot

# Multi-objective trade-off visualization
tradeoff_plot = {
    "type": "scatter",
    "data": alternatives_data,
    "x_axis": {"variable": "cost", "label": "Total Cost ($)"},
    "y_axis": {"variable": "benefit", "label": "Expected Benefit"},
    "options": {
        "show_pareto_frontier": True,
        "label_alternatives": True,
        "size_by": "probability",
        "color_by": "risk_category",
        "show_dominated_region": True
    }
}

Tornado Diagram

# Sensitivity tornado diagram
tornado = {
    "type": "tornado",
    "base_value": 1000000,
    "sensitivities": {
        "Price": {"low": 800000, "high": 1300000},
        "Volume": {"low": 900000, "high": 1150000},
        "Cost": {"low": 950000, "high": 1100000},
        "Market Share": {"low": 850000, "high": 1200000}
    },
    "options": {
        "sort_by": "swing",
        "show_base_line": True,
        "color_scheme": ["red", "green"],
        "show_values": True
    }
}

Uncertainty Visualization

# Distribution and confidence visualization
uncertainty_viz = {
    "type": "distribution",
    "data": simulation_results,
    "options": {
        "show_histogram": True,
        "show_density": True,
        "show_percentiles": [5, 25, 50, 75, 95],
        "show_mean": True,
        "confidence_band": 0.90,
        "highlight_threshold": 0  # e.g., breakeven
    }
}

Visualization Types

Type	Use Case	Key Features
Decision Tree	Structure visualization	Nodes, branches, payoffs
Strategy Table	Alternative comparison	Color-coded performance
Tornado Diagram	Sensitivity ranking	Horizontal bars, swing
Spider/Radar	Multi-criteria profile	Polygon overlay
Heat Map	Matrix data	Color intensity
Waterfall	Value decomposition	Sequential bars
Scatter	Trade-offs	Points, Pareto frontier
Box Plot	Uncertainty	Quartiles, outliers
Fan Chart	Forecast uncertainty	Widening confidence bands

Input Schema

{
  "visualization_type": "string",
  "data": "object",
  "axes": {
    "x": {"variable": "string", "label": "string"},
    "y": {"variable": "string", "label": "string"}
  },
  "options": {
    "title": "string",
    "color_scheme": "string",
    "interactive": "boolean",
    "annotations": ["object"],
    "export_format": "png|svg|pdf|html"
  }
}

Output Schema

{
  "visualization_path": "string",
  "interactive_url": "string (if applicable)",
  "metadata": {
    "type": "string",
    "dimensions": {"width": "number", "height": "number"},
    "data_summary": "object"
  },
  "accessibility": {
    "alt_text": "string",
    "data_table": "object"
  }
}

Design Principles

Clarity: Remove chart junk, maximize data-ink ratio
Accuracy: No distortion, appropriate scales
Efficiency: Quick comprehension, key insights prominent
Actionability: Clear implications for decisions
Accessibility: Color-blind friendly, alt text provided

Best Practices

Match visualization type to data and message
Use consistent color schemes across related charts
Include clear titles and axis labels
Highlight key takeaways with annotations
Provide interactive features for exploration
Export to multiple formats for different uses
Include data tables for accessibility

Integration Points

Receives data from all analysis skills
Feeds into Data Storytelling for narratives
Supports Executive Dashboard Development
Connects with Decision Journal for documentation