AgentSkillsCN

graph-modeler

将问题描述转化为图结构表示

SKILL.md
--- frontmatter
name: graph-modeler
description: Convert problem descriptions into graph representations
allowed-tools:
  - Read
  - Write
  - Grep
  - Glob

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

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

Output Schema

json
{
  "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"]
}