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graph-modeler

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Convert problem descriptions into graph representations

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Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/algorithms-optimization/skills/graph-modeler/SKILL.md

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Graph Modeler Skill

Purpose

Convert problem descriptions into appropriate graph representations, identifying entities as nodes and relationships as edges.

Capabilities

  • Entity-to-node mapping from problem text
  • Relationship-to-edge mapping
  • Graph property detection (bipartite, DAG, tree, etc.)
  • Suggest optimal representation (adjacency list vs matrix)
  • Generate graph visualization
  • Identify implicit graph structures

Target Processes

  • graph-modeling
  • shortest-path-algorithms
  • graph-traversal
  • advanced-graph-algorithms

Graph Modeling Framework

  1. Entity Identification: What objects/states become nodes?
  2. Relationship Analysis: What connections become edges?
  3. Edge Properties: Directed? Weighted? Capacities?
  4. Graph Properties: Special structure to exploit?
  5. Representation Choice: List vs matrix vs implicit?

Input Schema

{
  "type": "object",
  "properties": {
    "problemDescription": { "type": "string" },
    "constraints": { "type": "object" },
    "examples": { "type": "array" },
    "outputFormat": {
      "type": "string",
      "enum": ["analysis", "code", "visualization"]
    }
  },
  "required": ["problemDescription"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "nodes": { "type": "object" },
    "edges": { "type": "object" },
    "properties": {
      "type": "object",
      "properties": {
        "directed": { "type": "boolean" },
        "weighted": { "type": "boolean" },
        "bipartite": { "type": "boolean" },
        "dag": { "type": "boolean" },
        "tree": { "type": "boolean" }
      }
    },
    "representation": { "type": "string" },
    "suggestedAlgorithms": { "type": "array" }
  },
  "required": ["success"]
}