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+
Understand Anything
+
+
+ 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.
+
+
+
+ Understand Anything. Understand Anyone.
+
+ AI should help people, not replace them.
+
+ An open-source project from Egonex
+
+ Originally created by Lum1104.
+
+
+---
+
+**You just joined a new team. The codebase is 200,000 lines of code. Where do you even start?**
+
+Understand Anything is a [Claude Code Plugin](https://code.claude.com/docs/en/plugins-reference#plugins-reference) 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.**
+
+---
+
+## ✨ Features
+
+> [!NOTE]
+> **Want to skip the reading?** Try the [live demo](https://understand-anything.com/demo/) in our [homepage](https://understand-anything.com/) — a fully interactive dashboard you can pan, zoom, search, and explore right in your browser.
+
+### Explore the structural graph
+
+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.
+
+### Understand business logic
+
+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.
+
+### Analyze knowledge bases
+
+Point `/understand-knowledge` at a [Karpathy-pattern LLM wiki](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f) 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.
+
+
+
+
+
🧭 Guided Tours
+
Auto-generated walkthroughs of the architecture, ordered by dependency. Learn the codebase in the right order.
+
+
+
🔍 Fuzzy & Semantic Search
+
Find anything by name or by meaning. Search "which parts handle auth?" and get relevant results across the graph.
+
+
+
+
+
📊 Diff Impact Analysis
+
See which parts of the system your changes affect before you commit. Understand ripple effects across the codebase.
+
+
+
🎭 Persona-Adaptive UI
+
The dashboard adjusts its detail level based on who you are — junior dev, PM, or power user.
+
+
+
+
+
🏗️ Layer Visualization
+
Automatic grouping by architectural layer — API, Service, Data, UI, Utility — with color-coded legend.
+
+
+
📚 Language Concepts
+
12 programming patterns (generics, closures, decorators, etc.) explained in context wherever they appear.
+
+
+
+
+---
+
+## 🚀 Quick Start
+
+### 1. Install the plugin
+
+```bash
+/plugin marketplace add Egonex-AI/Understand-Anything
+/plugin install understand-anything
+```
+
+> **Using a local model?** For privacy or enterprise setups, point your platform at a local model provider such as [Ollama](https://docs.ollama.com/integrations) — follow their integration guide to change the model provider.
+
+### 2. Analyze your codebase
+
+```bash
+/understand
+```
+
+A multi-agent pipeline scans your project, extracts every file, function, class, and dependency, then builds a knowledge graph saved to `.ua/knowledge-graph.json`. (Projects that already have a `.understand-anything/` directory keep using it — it stays the data directory when present, so nothing needs migrating.)
+
+> **Heads up on token usage:** The initial `/understand` analyzes your whole codebase and can consume a significant number of tokens on large projects. We recommend running it on a token plan / subscription, or using a local model (see above) for initialization. Subsequent runs are incremental by default — only changed files are re-analyzed — so they use far fewer tokens.
+
+**Localized output:** Use `--language` to generate content in your preferred language:
+
+```bash
+# Generate Chinese content (知识图节点描述和 Dashboard UI)
+/understand --language zh
+
+# Supported languages: en (default), zh, zh-TW, ja, ko, ru
+```
+
+On the **first run** in a project — when you don't pass `--language` and no language is stored yet — `/understand` detects the language you're conversing in. If it isn't English, it asks you to confirm (or override) before generating; English conversations are unaffected. Your choice is saved to `.ua/config.json` and reused on every later run.
+
+The `--language` parameter affects:
+- Node summaries and descriptions in the knowledge graph
+- Dashboard UI labels, buttons, and tooltips
+- Guided tour explanations
+
+### 3. Explore the dashboard
+
+```bash
+/understand-dashboard
+```
+
+An interactive web dashboard opens with your codebase visualized as a graph — color-coded by architectural layer, searchable, and clickable. Select any node to see its code, relationships, and a plain-English explanation.
+
+### 4. Keep learning
+
+```bash
+# Ask anything about the codebase
+/understand-chat How does the payment flow work?
+
+# Analyze impact of your current changes
+/understand-diff
+
+# Deep-dive into a specific file or function
+/understand-explain src/auth/login.ts
+
+# Generate an onboarding guide for new team members
+/understand-onboard
+
+# Extract business domain knowledge (domains, flows, steps)
+/understand-domain
+
+# Analyze a Karpathy-pattern LLM wiki knowledge base
+/understand-knowledge ~/path/to/wiki
+
+# Re-run anytime — incremental by default (only re-analyzes changed files)
+/understand
+
+# Auto-update on every commit via a post-commit hook
+/understand --auto-update
+
+# Scope to a subdirectory (for huge monorepos)
+/understand src/frontend
+```
+
+---
+
+## 🌐 Multi-Platform Installation
+
+Understand-Anything works across multiple AI coding platforms.
+
+### Claude Code (Native)
+
+```bash
+/plugin marketplace add Egonex-AI/Understand-Anything
+/plugin install understand-anything
+```
+
+
+### One-line install (Codex / OpenCode / OpenClaw / Antigravity / Gemini CLI / Pi Agent / Vibe CLI / VS Code Copilot / Hermes / Cline / KIMI CLI / Trae / Nanobot / Kiro)
+
+
+**macOS / Linux:**
+```bash
+curl -fsSL https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/install.sh | bash
+# or skip the prompt by passing the platform:
+curl -fsSL https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/install.sh | bash -s codex
+```
+
+**Windows (PowerShell):**
+```powershell
+iwr -useb https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/install.ps1 | iex
+```
+
+The installer clones the repo to `~/.understand-anything/repo` and creates the right symlinks for the chosen platform. Restart your CLI/IDE afterwards.
+
+> **Note on invoking skills:** the invocation prefix differs per platform. Most platforms use slash commands (`/understand`), but **Codex uses `$` instead** — type `$understand`, not `/understand`. If neither prefix is recognized on your platform, just ask in plain language: *"Use the understand skill to analyze this project."*
+
+- Supported `` values: `gemini`, `codex`, `opencode`, `pi`, `openclaw`, `antigravity`, `vibe`, `vscode`, `hermes`, `cline`, `kimi`, `trae`, `nanobot`, `kiro`
+- Update later: `./install.sh --update`
+- Uninstall: `./install.sh --uninstall `
+
+### Cursor
+
+Cursor auto-discovers the plugin via `.cursor-plugin/plugin.json` when this repo is cloned. No manual installation needed — just clone and open in Cursor.
+
+If auto-discovery doesn't pick it up, install it manually: open **Cursor Settings → Plugins**, paste `https://github.com/Egonex-AI/Understand-Anything` into the search field, and add it from there.
+
+### VS Code + GitHub Copilot
+
+VS Code with GitHub Copilot (v1.108+) auto-discovers the plugin via `.copilot-plugin/plugin.json` when this repo is cloned. No manual installation needed — just clone and open in VS Code.
+
+For personal skills (available across all projects), run the `install.sh` above with the `vscode` platform.
+
+### Copilot CLI
+
+```bash
+copilot plugin install Egonex-AI/Understand-Anything:understand-anything-plugin
+```
+
+### Kiro CLI / IDE
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/install.sh | bash -s kiro
+```
+
+After installation:
+- **Kiro CLI**: `kiro-cli chat --agent understand "Analyze this project"`
+- **Kiro IDE**: The skills are symlinked into `~/.kiro/skills/` and the `understand` agent is written to `~/.kiro/agents/understand.json`, so both are available after restarting the IDE.
+
+For personal skills (available across all projects), run the `install.sh` above with the `kiro` platform.
+
+### Platform Compatibility
+
+| Platform | Status | Install Method |
+|----------|--------|----------------|
+| Claude Code | ✅ Native | Plugin marketplace |
+| Cursor | ✅ Supported | Auto-discovery |
+| VS Code + GitHub Copilot | ✅ Supported | Auto-discovery |
+| Copilot CLI | ✅ Supported | Plugin install |
+| Codex | ✅ Supported | `install.sh codex` |
+| OpenCode | ✅ Supported | `install.sh opencode` |
+| OpenClaw | ✅ Supported | `install.sh openclaw` |
+| Antigravity | ✅ Supported | `install.sh antigravity` |
+| Gemini CLI | ✅ Supported | `install.sh gemini` |
+| Pi Agent | ✅ Supported | `install.sh pi` |
+| Vibe CLI | ✅ Supported | `install.sh vibe` |
+| Hermes | ✅ Supported | `install.sh hermes` |
+| Cline | ✅ Supported | `install.sh cline` |
+| KIMI CLI | ✅ Supported | `install.sh kimi` |
+| Trae | ✅ Supported | `install.sh trae` |
+| Nanobot | ✅ Supported | `install.sh nanobot` |
+| Kiro CLI / IDE | ✅ Supported | `install.sh kiro` |
+
+
+---
+
+## 📦 Share the Graph with Your Team
+
+The graph is just JSON — **commit it once, and teammates skip the pipeline**. Good for onboarding, PR reviews, and docs-as-code.
+
+> **Example:** [GoogleCloudPlatform/microservices-demo](https://github.com/GoogleCloudPlatform/microservices-demo) — Go / Java / Python / Node reference with a committed graph.
+
+**What to commit:** everything in `.ua/` *except* `intermediate/` and `diff-overlay.json` (those are local scratch). (Legacy projects use `.understand-anything/` — substitute that directory name below if it's the one present.)
+
+```gitignore
+.ua/intermediate/
+.ua/diff-overlay.json
+```
+
+**Keep it fresh:** enable `/understand --auto-update` — a post-commit hook incrementally patches the graph so each commit lands with a matching graph. Or re-run `/understand` manually before releases.
+
+**Large graphs (10 MB+):** track with **git-lfs**.
+
+```bash
+git lfs install
+git lfs track ".ua/*.json"
+git add .gitattributes .ua/
+```
+
+### View the dashboard without Claude Code
+
+Once a graph has been generated and committed, anyone on the team can open it with one command — no Claude Code, no LLM, no API key. Only Node.js (>= 18) is required:
+
+```bash
+npx https://github.com/Egonex-AI/Understand-Anything/releases/latest/download/understand-anything-viewer.tgz /path/to/analyzed/project
+```
+
+The terminal prints a tokenized URL (`http://127.0.0.1:5173/?token=…`) and opens the full interactive dashboard in your browser. The project directory (default: current directory) must contain the committed data directory (`.ua/`, or legacy `.understand-anything/`). Everything is served read-only from local disk — no LLM calls, no data leaves your machine.
+
+Working from a clone instead? `pnpm install && pnpm --filter @understand-anything/core build`, then `GRAPH_DIR=/path/to/analyzed/project pnpm dev:dashboard` does the same via the Vite dev server.
+
+---
+
+## 🔧 Under the Hood
+
+### Tree-sitter + LLM hybrid
+
+Static analysis and LLMs do what each does best:
+
+- **Tree-sitter (deterministic)** — parses source into a concrete syntax tree and extracts structural facts: imports, exports, function/class definitions, call sites, inheritance. Pre-resolved into an `importMap` during the scan phase and passed to file-analyzers so they don't re-derive imports from source. Same input → same output, every run. Also powers fingerprint-based change detection for incremental updates.
+- **LLM (semantic)** — reads the parsed structure alongside the original source to produce what parsers can't: plain-English summaries, tags, architectural layer assignments, business-domain mapping, guided tours, language concept callouts.
+
+This split is why the graph is reproducible on the structural side (the same code always yields the same edges) while still capturing intent on the semantic side (what a file is *for*, not just what it imports).
+
+### Multi-Agent Pipeline
+
+The `/understand` command orchestrates 5 specialized agents, and `/understand-domain` adds a 6th:
+
+| Agent | Role |
+|-------|------|
+| `project-scanner` | Discover files, detect languages and frameworks |
+| `file-analyzer` | Extract functions, classes, imports; produce graph nodes and edges |
+| `architecture-analyzer` | Identify architectural layers |
+| `tour-builder` | Generate guided learning tours |
+| `graph-reviewer` | Validate graph completeness and referential integrity (runs inline by default; use `--review` for full LLM review) |
+| `domain-analyzer` | Extract business domains, flows, and process steps (used by `/understand-domain`) |
+| `article-analyzer` | Extract entities, claims, and implicit relationships from wiki articles (used by `/understand-knowledge`) |
+
+File analyzers run in parallel (up to 5 concurrent, 20-30 files per batch). Supports incremental updates — only re-analyzes files that changed since the last run.
+
+---
+
+## 🎥 Community
+
+A community-made walkthrough by **Better Stack**.
+
+
+
+Made a video, blog post, or tutorial? Open an issue or PR — happy to feature it here.
+
+---
+
+## 🤝 Contributing
+
+Contributions are welcome! Here's how to get started:
+
+1. Fork the repository
+2. Create a feature branch (`git checkout -b feature/my-feature`)
+3. Run the tests (`pnpm --filter @understand-anything/core test`)
+4. Commit your changes and open a pull request
+
+Please open an issue first for major changes so we can discuss the approach.
+
+---
+
+
+
+