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graph-modeler

Turn a problem description into a graph by identifying its objects and connections. The skill can classify graph properties, suggest a suitable storage format such as a list or matrix, and point to relevant algorithms for analysis or implementation.

OriginalShow the original description

Convert problem descriptions into graph representations

Run score Not tested

See how to install

Good for

  • Modeling a problem as nodes and edges
  • Choosing a graph storage format
  • Identifying graph properties and useful algorithms

Files included (2)

  • SKILL.md2.1 KB
  • README.md706 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

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"]
}

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