graph
✓Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis.
Installation
SKILL.md
Systematic extraction and analysis of entities, relationships, and ontological structures from unstructured text—enhanced with categorical metagraph compression enabling scale-invariant representation through structural equivalence, k-bisimulation summarization, and quotient constructions that preserve query-answering capabilities while achieving dramatic size reductions.
Structural equivalence enables compression through a precise mechanistic chain:
Graphs with large automorphism groups have lower complexity because only one representative from each orbit needs encoding. For highly symmetric structures, compression can reach n/log n factor.
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis. Source: zpankz/mcp-skillset.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/zpankz/mcp-skillset --skill graph- Source
- zpankz/mcp-skillset
- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is graph?
Use when extracting entities and relationships, building ontologies, compressing large graphs, or analyzing knowledge structures - provides structural equivalence-based compression achieving 57-95% size reduction, k-bisimulation summarization, categorical quotient constructions, and metagraph hierarchical modeling with scale-invariant properties. Supports recursive refinement through graph topology metrics including |R|/|E| ratios and automorphism analysis. Source: zpankz/mcp-skillset.
How do I install graph?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/zpankz/mcp-skillset --skill graph Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/zpankz/mcp-skillset
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01