Skillget

nium-wiki

skill
Guvenlik Denetimi
Basarisiz
Health Uyari
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 8 GitHub stars
Code Basarisiz
  • process.env — Environment variable access in scripts/inject-version.mjs
  • fs.rmSync — Destructive file system operation in scripts/post-bundle.mjs
  • fs.rmSync — Destructive file system operation in src/cli.ts
  • exec() — Shell command execution in src/commands/analyzeModule.ts
  • exec() — Shell command execution in src/core/buildDeps.ts
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This tool is an AI coding assistant skill that transforms a local codebase into a fully cross-referenced, structured wiki. It automatically analyzes project dependencies, generates documentation with diagrams, and tracks changes using SHA256 hashing.

Security Assessment
Overall Risk: Medium. The tool makes no external network requests, claims to be fully offline, and does not ask for dangerous system permissions. However, the rule-based audit flags several notable code behaviors. It relies on `exec()` to run shell commands during module analysis and dependency building. It also uses `fs.rmSync` to perform destructive file system operations, likely to clean up temporary files or rebuild the wiki directory. Environment variables are accessed in build scripts, which is standard, but users should still be cautious of what commands are executed in the background.

Quality Assessment
The project is licensed under the permissive MIT license and is actively maintained, with its most recent push occurring today. However, community trust and visibility are currently very low. With only 8 GitHub stars, the tool is still in its early stages and has not been widely tested or vetted by the broader developer community.

Verdict
Use with caution — it operates entirely offline, but execute it in a sandboxed environment to protect your file system from its destructive delete operations and dynamic shell executions.
SUMMARY

AI coding tool skill (e.g., Claude Code) centered on Karpathy's LLM Wiki pattern turns codebases into wikis, auto-analyzes, and generates docs similar to DeepWiki and ZRead with diagrams.

README.md

Nium-Wiki Logo

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
  • ⚡ Incremental Updates: SHA256-based change detection for efficient regeneration
  • 💡 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
  • 🔒 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
└── 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.

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
}
Field Type Default Description
language string en Documentation language. Supports zh, en, ja, ko, fr, de. Use / for multi-language, e.g. zh/en (primary Chinese, secondary English)
exclude string[] see above Directories to exclude from code analysis and doc generation
useGitignore boolean true Automatically read .gitignore directory rules and merge into the exclude list

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.

Scenario Token Cost Notes
First generation (with Explore context) Moderate The AI tool already understands the project structure, jumping straight to doc generation. Cost depends on project size
First generation (fresh project) Higher Requires a full code reading and analysis pass — essentially a deep Explore + doc generation
Incremental updates Very low Detects code changes via SHA256 hashing, pinpoints affected docs for targeted updates
Multi-language translation Very low Translates after primary language docs are complete, also supports incremental update logic

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: Explicitly model document organization rules as a first-class schema for more precise and consistent incremental updates

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

Generated with ❤️ by Nium-Wiki

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