nium-wiki
Automatically transforms codebases into searchable, documented wikis with AI-generated diagrams and analysis, reducing manual documentation overhead and onbo…
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.
- Generate automatic documentation from existing codebase files and structure.
- Create visual diagrams explaining code architecture and component relationships.
- Build searchable wiki pages from source code analysis without manual writing.
Automatically transforms codebases into searchable, documented wikis with AI-generated diagrams and analysis, reducing manual documentation overhead and onboarding time for teams inheriting or scaling complex systems.
Engineering teams managing large or unfamiliar codebases seeking faster comprehension and knowledge sharing without dedicated documentation effort.
https://github.com/niuma996/nium-wiki
By niuma996
How to Get It
claude plugins install niuma996/nium-wiki
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate automatic documentation from existing codebase files and structure
Trust Signals Auto-scanned
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 4d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
- Single maintainer. Consider the risk if this person stops maintaining the project.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 4d ago; license MIT.