Index unstructured files into a persistent knowledge graph with audit trails.
npx skills add https://github.com/andrew-t-james/dotfiles --skill graphify-andrew-t-james
Please help me install this Agent Skill. Skill: graphify Source: https://github.com/andrew-t-james/dotfiles/tree/main/dot_claude/skills/graphify Command: npx skills add https://github.com/andrew-t-james/dotfiles --skill graphify-andrew-t-james
Transform disparate code, docs, papers, and media into a structured knowledge graph with persistent provenance and an audit trail, enabling cross-document discovery and project-wide visibility.
Drop your target folder into graphify and run the full pipeline to generate an interactive graph, a JSON export, and an audit report.
High-intent search queries and answers about installing and using this skill.
To build a knowledge graph from mixed files, index unstructured code, docs, and media into a persistent, queryable structure. This process applies deterministic AST extraction and semantic extraction to map relationships across your entire project folder.
Knowledge graph extraction transforms unstructured data into structured nodes and edges. It uses an Agent-driven pipeline to apply semantic extraction and deterministic AST extraction, enabling cross-document discovery and clustering from disparate files.
Yes, you can visualize relationships across a codebase and research archives simultaneously. The pipeline indexes mixed-content folders into a persistent graph state, applies community detection, and exports the results to an interactive HTML visualization.
To generate an audit trail for cross-document discovery, run the full extraction and clustering pipeline. It produces a readable audit report alongside interactive HTML and JSON exports, providing persistent provenance for your project portfolio.
Knowledge graph visualization suits auditing a project portfolio across mixed files like PDFs, images, and code. It indexes these unstructured formats into a queryable graph with provenance, ensuring end-to-end reporting and visibility.
The best way to onboard a codebase using graph analysis is to run an extraction pipeline that maps the code into a navigable graph. This enables structured storytelling and cross-document discovery through an interactive HTML output.
NoegnesisBuilds a navigable knowledge graph from mixed folders with HTML and JSON exports.
BarrettLoweConvert code, documents, papers, and images into structured knowledge graphs with community detection.
microsoftBuild a knowledge graph from mixed files with an explicit audit trail.
darelabs-techMine brownfield software patterns via AST analysis to generate architectural documentation and JSON facts.
