REPOGEO REPORT · LITE
lucasastorian/llmwiki
Default branch master · commit 0b14c925 · scanned 6/1/2026, 6:23:00 AM
GitHub: 1,002 stars · 169 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface lucasastorian/llmwiki, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition the README's opening statement to clarify its role as an AI-powered wiki application.
Why:
CURRENT# LLM Wiki [](https://opensource.org/licenses/Apache-2.0) Open-source implementation of Karpathy's LLM Wiki (spec).
COPY-PASTE FIX# LLM Wiki: Your AI-Powered Research Wiki Generator [](https://opensource.org/licenses/Apache-2.0) LLM Wiki is an open-source AI application that automatically generates and maintains a comprehensive wiki from your research documents, leveraging LLMs like Claude via MCP. It offloads the tedious work of summarizing, linking, and citing, allowing you to focus on source selection and analysis.
- mediumcomparison#2Add a 'Comparison' section to the README.
Why:
COPY-PASTE FIXAdd a new section to your README, perhaps titled 'How LLM Wiki Compares' or 'Why LLM Wiki?', that explicitly contrasts it with foundational LLM libraries (like LlamaIndex or LangChain) by highlighting its role as a complete, end-user application, and differentiates it from manual note-taking tools (like Obsidian) by emphasizing its automated wiki generation and maintenance capabilities.
- lowabout#3Refine the repository description.
Why:
CURRENTOpen Source Implementation of Karpathy's LLM Wiki. Upload documents, connect your Claude account via MCP, and have it write your wiki !
COPY-PASTE FIXAn open-source AI application that automatically generates and maintains a comprehensive wiki from your research documents, leveraging LLMs like Claude via MCP.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- LlamaIndex · recommended 2×
- LangChain · recommended 2×
- Hugging Face Transformers · recommended 2×
- Obsidian · recommended 1×
- Smart Connections · recommended 1×
- CATEGORY QUERYHow can I automatically generate and maintain a wiki from my research documents using AI?you: not recommendedAI recommended (in order):
- Obsidian
- Smart Connections
- Text Generator
- OpenAI GPT-4
- Anthropic Claude
- Dataview
- Pandoc
- Mem.ai
- Notion
- Notion AI
- Zapier
- Make
- OpenAI API
- PyPDF2
- python-docx
- markdown
- LlamaIndex
- LangChain
- ChromaDB
- Pinecone
- FAISS
- GPT-3.5
- Hugging Face Transformers
- MkDocs
- Jekyll
- Hugo
- Confluence
- Aura
- K15t Scroll Viewport
- Logseq
- Logseq AI Assistant
- Dendron
- VS Code
- GitHub Copilot
AI recommended 34 alternatives but never named lucasastorian/llmwiki. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are open-source tools for building an AI agent that summarizes and cross-references my local files?you: not recommendedAI recommended (in order):
- LlamaIndex
- LangChain
- Hugging Face Transformers
- Sentence-Transformers
- Chroma
- Faiss
- Apache Solr
- Elasticsearch
AI recommended 8 alternatives but never named lucasastorian/llmwiki. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of lucasastorian/llmwiki?passAI named lucasastorian/llmwiki explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts lucasastorian/llmwiki in production, what risks or prerequisites should they evaluate first?passAI named lucasastorian/llmwiki explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo lucasastorian/llmwiki solve, and who is the primary audience?passAI named lucasastorian/llmwiki explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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lucasastorian/llmwiki — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite