RRepoGEO

REPOGEO REPORT · LITE

lewislulu/llm-wiki-skill

Default branch main · commit d7751c0a · scanned 6/12/2026, 10:58:26 AM

GitHub: 582 stars · 102 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 lewislulu/llm-wiki-skill, 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.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["llm-agent", "knowledge-base", "wiki", "llm-compilation", "anti-rag", "openclaw", "codex", "karpathy"]
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0). This is essential for users to understand usage rights and for AI to correctly identify the project's legal status.
  • mediumabout#3
    Clarify the 'About' description to highlight core differentiators

    Why:

    CURRENT
    Karpathy-style LLM knowledge base Agent Skill for OpenClaw/Codex. Experimental — will iterate over time.
    COPY-PASTE FIX
    An OpenClaw/Codex Agent Skill for building persistent, LLM-compiled knowledge bases, replacing RAG with a self-improving, cross-linked Markdown wiki. Experimental.

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.

Recall
0 / 2
0% of queries surface lewislulu/llm-wiki-skill
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. pinecone-io/pinecone-python-client · recommended 1×
  3. weaviate/weaviate · recommended 1×
  4. chroma-core/chroma · recommended 1×
  5. openai/openai-python · recommended 1×
  • CATEGORY QUERY
    How to build a persistent, self-improving knowledge base using large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Pinecone (pinecone-io/pinecone-python-client)
    3. Weaviate (weaviate/weaviate)
    4. ChromaDB (chroma-core/chroma)
    5. OpenAI (openai/openai-python)
    6. Anthropic (anthropics/anthropic-python)
    7. GPT-4
    8. Claude 3
    9. Llama 3
    10. LlamaIndex (run-llama/llama_index)
    11. Milvus (milvus-io/milvus)
    12. Qdrant (qdrant/qdrant)
    13. Supabase (supabase/supabase)
    14. pgvector (pgvector/pgvector)
    15. Cohere (cohere-ai/cohere-python)
    16. Google Gemini
    17. PostgreSQL
    18. scikit-learn (scikit-learn/scikit-learn)
    19. Haystack (deepset-ai/haystack)
    20. Elasticsearch (elastic/elasticsearch)
    21. FAISS (facebookresearch/faiss)
    22. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    23. Azure OpenAI Service
    24. Azure Cosmos DB
    25. Azure Cognitive Search
    26. Hugging Face Transformers (huggingface/transformers)
    27. Sentence-Transformers (UKPLab/sentence-transformers)
    28. Mistral
    29. T5
    30. Falcon

    AI recommended 30 alternatives but never named lewislulu/llm-wiki-skill. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool for AI-assisted compilation of raw text into a structured, cross-linked wiki.
    you: not recommended
    AI recommended (in order):
    1. Obsidian
    2. Notion
    3. Logseq
    4. Mem.ai
    5. Confluence
    6. MediaWiki
    7. DokuWiki
    8. OpenAI GPT-4
    9. Anthropic Claude

    AI recommended 9 alternatives but never named lewislulu/llm-wiki-skill. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

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 lewislulu/llm-wiki-skill?
    pass
    AI named lewislulu/llm-wiki-skill explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts lewislulu/llm-wiki-skill in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name lewislulu/llm-wiki-skill — likely talking about a different project

    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 lewislulu/llm-wiki-skill solve, and who is the primary audience?
    pass
    AI did not name lewislulu/llm-wiki-skill — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Brand-free category queries5 vs 2 in Lite
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