Convert code, docs, papers, and images into knowledge graphs with community detection.
npx skills add https://github.com/ttww97/skill-manager --skill graphify-ttww97
Please help me install this Agent Skill. Skill: graphify Source: https://github.com/ttww97/skill-manager/tree/main/graphify Command: npx skills add https://github.com/ttww97/skill-manager --skill graphify-ttww97
This Skill turns various types of inputs, such as code, documents, papers, and images, into a structured knowledge graph, enabling users to discover and explore interconnected concepts and relationships.
Run the 'graphify' command in the directory containing your files to generate a knowledge graph.
High-intent search queries and answers about installing and using this skill.
To generate a knowledge graph from code and documents, run the graphify command in your target directory to parse inputs and identify clusters of related concepts automatically.
Community detection in code analysis identifies clusters of related concepts within a knowledge graph, helping you discover interconnected components and understand new codebase architecture.
Yes, you need Python, the graphifyy library, and Neo4j installed, as parsing code, documents, papers, and images into a knowledge graph requires these dependencies for analysis.
Yes, you can convert image inputs into an interactive HTML knowledge graph, generating interactive HTML, JSON, and audit reports to explore interconnected concepts visually.
The best way to analyze a new codebase architecture is transforming its components into a knowledge graph, which identifies related concept communities and provides interactive reports for exploration.
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