Nium-Wiki

English | 中文

A skill for AI coding tools (e.g., Claude Code) that turns codebases into high-quality wikis. Auto-analyzes structure, generates docs with diagrams and cross-references. Inspired by DeepWiki, ZRead, Code Wiki.

Features

• 🚀 Deep Code Analysis: Semantic understanding of your codebase, beyond syntax parsing
• 📊 Mermaid Diagrams: Auto-generated architecture, data flow, and dependency diagrams
• 🔗 Cross-linked Documentation: Bidirectional links between docs with source traceability
• ⚡ Idempotent Incremental Updates: Safe to re-run anytime — SHA256 diff + dep-graph propagation rewrite only the pages affected by code changes, preserving every other doc untouched
• ➕ Additive by Design: New modules, new secondary languages, and hand-edited domain pages coexist across re-runs — no full-wiki rebuild, no clobbering existing content
• 💡 Compiled, Not Retrieved: Aligned with the Karpathy LLM Wiki pattern — docs are compiled upfront, updated incrementally
• 🌐 Multi-language Support: Works with JS/TS/Python/Go/Rust/Java and 10+ languages
• 🧭 Import-Graph Module Discovery: Language-agnostic module discovery via dependency graph, paired with two-phase fact extraction for accurate API docs
• 🔒 Fully Offline: Zero external dependencies, works in air-gapped environments
• 📝 Professional Output: Enterprise-grade documentation with automated quality auditing

Quick Start

Installation

Before using Nium-Wiki, you need to add it as a skill to your AI coding tool:

npx skills add https://github.com/niuma996/nium-wiki --skill nium-wiki

Nium-Wiki works as an AI coding tool skill (e.g. Claude Code). Just tell the AI:

# In Claude Code, say:
> generate wiki
> create docs
> update wiki
> rebuild wiki

The skill will automatically run the full workflow: init → analyze → deep code reading → generate docs → build index → audit quality.

For incremental updates after code changes:

> update wiki

Changed files are detected via SHA256 hashing. The incremental command combines diff analysis, dependency graph traversal, and doc-to-doc propagation to pinpoint affected wiki pages — regenerating only what changed, nothing more.

Generated Output Structure

.nium-wiki/
├── config.json              # Language & exclude settings
├── meta.json                # Version, timestamps, stats
├── cache/
│   ├── structure.json       # Project structure snapshot
│   ├── source-index.json    # SHA256 file hashes (change detection)
│   ├── doc-index.json       # Source ↔ Doc bidirectional mapping
│   ├── dep-graph.json       # Import/require dependency graph
│   └── facts/               # Per-module fact extraction cache
└── wiki/                    # Generated documentation
    ├── index.md             # Project homepage
    ├── architecture.md      # System architecture + Mermaid diagrams
    ├── getting-started.md   # Quick start guide
    ├── doc-map.md           # Documentation relationship map
    ├── api/                 # API reference docs
    ├── <domain>/            # Domain-organized module docs
    │   ├── _index.md        # Domain overview
    │   └── <module>.md      # Module documentation
    └── ...

Multi-language Support

# Initialize with primary (first) + secondary language
npx nium-wiki init --lang zh/en

Secondary language docs are generated in wiki_{lang}/ directories (e.g. .nium-wiki/wiki_en/), mirroring the same structure as wiki/.

Local Preview

# Install
npm install -g nium-wiki

# Start local documentation server (default port 4000)
npx nium-wiki serve

# Specify port
npx nium-wiki serve --port 3000

# Specify wiki directory
npx nium-wiki serve .nium-wiki/wiki

Open http://localhost:4000 in your browser to preview the generated docs, with full-text search, sidebar navigation, Mermaid diagram rendering, and a source code drawer that opens when you click any source file link in the wiki.

Relationship Graph

Click the Graph button in the top-right corner of the preview server to open an interactive relationship graph at /_graph.

The graph visualizes all nodes and edges extracted from your project:

• Blue nodes — source code files (.ts, .js, .py, etc.)
• Orange nodes — documentation files (.md)
• Edges — three relationship types:
  • import — one source file imports another
  • refers — a doc file references a source file (or vice versa)
  • links — a doc file links to another doc file

For large projects (> 500 nodes), the graph loads docs and their directly linked source nodes first, then expands outward via import edges until ~500 nodes are visible. Click any source node to reveal its hidden import neighbors on demand.

Click a node to highlight it: connected nodes stay at full color, unrelated nodes dim. The detail panel on the right shows incoming and outgoing edges for the selected node.

Wiki Generation Showcase

See claude-code-sourcemap-wiki for a live example of a full project generated with Nium-Wiki.

Configuration

After initialization, a default config is generated at .nium-wiki/config.json:

{
  "language": "zh",
  "exclude": [
    "node_modules", ".git", "dist", "build",
    "coverage", "__pycache__", "venv", ".venv"
  ],
  "useGitignore": true
}

In addition to custom excludes in config.json, the tool has built-in common exclude directories (.git, .idea, .vscode, node_modules, dist, etc.) and language-specific rules from each handler (e.g. Python's __pycache__, Go's vendor), so no manual configuration is needed for those.

Offline-First Design

Nium-Wiki is designed to work completely offline with zero external dependencies, perfect for enterprise internal networks and air-gapped environments:

Preview Server

• ✅ All frontend assets (Docsify, Prism.js, Mermaid) are bundled locally
• ✅ No CDN requests or external API calls

Token Cost

Nium-Wiki is designed to leverage the AI coding tool's existing understanding of your project (from the Explore process), guiding it to output documentation in a structured way — rather than analyzing the entire codebase from scratch.

For projects where you've been using an AI coding tool for a while, the first generation cost is typically reasonable. Day-to-day usage is dominated by incremental updates, which cost very little.

Upcoming Features

• Continuously optimizing documentation quality while reducing model interaction rounds
• Centralized documentation management service
• Intelligent search tooling (cross-project)
• Karpathy LLM Wiki Schema Layer: extend the existing module-facts schema to cover wiki organization rules (domain partitioning, section contracts, cross-doc relations) and drive section-level incremental updates from it

Use Cases

• Enterprise Documentation: Generate comprehensive docs for internal projects
• Open Source Projects: Maintain up-to-date documentation automatically
• Code Reviews: Visualize architecture and dependencies
• Onboarding: Help new developers understand the codebase
• Air-gapped Environments: Works completely offline

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT

Links

• GitHub Repository
• Issue Tracker

Generated with ❤️ by Nium-Wiki