graph-modeler
Convert problem descriptions into graph representations
npx skills add a5c-ai/babysitter --skill graph-modeler --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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
- Purpose
- Capabilities
- Target Processes
- Graph Modeling Framework
- Input Schema
- Output Schema
What does the graph-modeler skill do?
Convert problem descriptions into graph representations
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill graph-modeler --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.