Convert unstructured code, docs, and media into queryable knowledge graphs.
npx skills add https://github.com/automatedigital/spark --skill graphify-automatedigital
Please help me install this Agent Skill. Skill: graphify Source: https://github.com/automatedigital/spark/tree/main/.claude/skills/graphify Command: npx skills add https://github.com/automatedigital/spark --skill graphify-automatedigital
This Skill eliminates the tedious manual work of tracing relationships, dependencies, and architectural patterns across large codebases, scattered documentation, research papers, and multimedia content, turning unstructured project assets into an organized, queryable knowledge graph with community detection to surface hidden cross-document connections.
Use the graphify skill to build a queryable knowledge graph of your current project directory and receive a plain-language report of its architecture, key components, and cross-file relationships.
High-intent search queries and answers about installing and using this skill.
You can build a queryable knowledge graph from a large codebase by processing unstructured code files to extract dependencies, map architectural patterns, and perform community detection, resulting in a persistent graph with full audit trails for natural language querying.
The best way to map architectural dependencies across scattered documentation is converting docs, papers, and multimedia into a unified knowledge graph that surfaces hidden cross-document connections and traces shortest paths between concepts.
Yes, you can extract knowledge graphs from images and video alongside code. The Skill utilizes optional LLM subagents for semantic extraction on non-code assets, integrating them into the same persistent graph structure as the codebase analysis.
Yes, this codebase analysis tool exports to Neo4j and Obsidian. It generates Neo4j cypher scripts, optional Obsidian vaults, interactive HTML visualizations, and GraphRAG-ready JSON from the extracted knowledge graph.
To avoid re-extracting unchanged files when updating a knowledge graph, the Skill supports incremental updates. It processes only new or modified content while preserving existing node relationships and the audit trail.
A limitation of using community detection for codebase analysis is that clustering groups nodes by structural connections, which may obscure specific functional dependencies unless you explicitly trace the shortest path between individual concepts.
infantesromeroadrianConvert code, documents, papers, images, and videos into a structured knowledge graph.
itsmarsssExport an Obsidian vault's wikilink graph to JSON, GraphML, Cypher, and HTML.
tiroqTransform code, documents, and images into a persistent knowledge graph.
quangphu1912Detects circular dependencies, architectural violations, and conflicts in module graphs via static code analysis.
