By rkendel1
AI-powered codebase understanding — analyze, visualize, and explain any project
Analyzes a codebase's file structure, summaries, and import relationships to identify logical architectural layers and assign every file to exactly one layer.
Analyzes markdown files using pre-parsed structural data and LLM inference to extract knowledge graph nodes and edges (entities, claims, implicit relationships, topic clustering).
Reviews the output of merge-batch-graphs.py for semantic issues the script cannot catch. Recovers dropped nodes/edges and fills cross-batch gaps.
Analyzes codebases to extract business domain knowledge — domains, business flows, and process steps. Produces a domain-graph.json that maps how business logic flows through the code.
Analyzes batches of source files to produce knowledge graph nodes and edges. Extracts file structure, functions, classes, and relationships using a two-phase approach: structural extraction script followed by LLM semantic analysis.
Use when you need to ask questions about a codebase or understand code using a knowledge graph
Launch the interactive web dashboard to visualize a codebase's knowledge graph
Use when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks
Extract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
Use when you need a deep-dive explanation of a specific file, function, or module in the codebase
Executes bash commands
Hook triggers when Bash tool is used
Uses power tools
Uses Bash, Write, or Edit tools
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Turn any codebase, knowledge base, or docs into an interactive knowledge graph you can explore, search, and ask questions about.
Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
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You just joined a new team. The codebase is 200,000 lines of code. Where do you even start?
Understand Anything is a multi-platform coding assistant plugin/skill set that analyzes your project with a multi-agent pipeline, builds a knowledge graph of every file, function, class, and dependency, then gives you an interactive dashboard to explore it all visually. Stop reading code blind. Start seeing the big picture.
The goal isn't a graph that wows you with how complex your codebase is — it's a graph that quietly teaches you how every piece fits together.
[!NOTE] Want to skip the reading? Try the live demo in our homepage — a fully interactive dashboard you can pan, zoom, search, and explore right in your browser.
Navigate your codebase as an interactive knowledge graph — every file, function, and class is a node you can click, search, and explore. Select any node to see plain-English summaries, relationships, and guided tours.
Switch to the domain view and see how your code maps to real business processes — domains, flows, and steps laid out as a horizontal graph.
Point /understand-knowledge at a Karpathy-pattern LLM wiki and get a force-directed knowledge graph with community clustering. The deterministic parser extracts wikilinks and categories from index.md, then LLM agents discover implicit relationships, extract entities, and surface claims — turning your wiki into a navigable graph of interconnected ideas.
npx claudepluginhub rkendel1/graphing --plugin understand-anythingUltra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills.
Memory compression system for Claude Code - persist context across sessions
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns