RRepoGEO

REPOGEO REPORT · LITE

lucasastorian/llmwiki

Default branch master · commit 2c288b10 · scanned 7/1/2026, 6:28:06 AM

GitHub: 1,247 stars · 202 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 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.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 subtitle to emphasize "complete, autonomous application"

    Why:

    CURRENT
    **An autonomous, self-maintaining personal Wikipedia built and maintained by AI.**
    COPY-PASTE FIX
    **A complete, autonomous AI application for building and maintaining your personal Wikipedia.**
  • mediumreadme#2
    Add a "Why LLM Wiki?" section to explicitly differentiate from competitors

    Why:

    COPY-PASTE FIX
    Add a new section (e.g., "Why LLM Wiki?") with bullet points explaining its unique position as a complete, autonomous application, distinct from manual PKM tools and underlying LLM frameworks.
  • lowtopics#3
    Add more specific topics for better keyword matching

    Why:

    CURRENT
    agents, ai-agents, claude, karpathy, knowledge-base, llm, llm-wiki, mcp, mcp-server, rag, supabase
    COPY-PASTE FIX
    agents, ai-agents, claude, karpathy, knowledge-base, llm, llm-wiki, mcp, mcp-server, rag, supabase, personal-knowledge-base, autonomous-ai, ai-system

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 lucasastorian/llmwiki
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Obsidian
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Obsidian · recommended 1×
  2. Mem.ai · recommended 1×
  3. Logseq · recommended 1×
  4. Notion · recommended 1×
  5. Roam Research · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered personal knowledge base that self-updates from my readings?
    you: not recommended
    AI recommended (in order):
    1. Obsidian
    2. Mem.ai
    3. Logseq
    4. Notion
    5. Roam Research
    6. TiddlyWiki

    AI recommended 6 alternatives but never named lucasastorian/llmwiki. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an autonomous system to organize documents and provide context for large language models.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Weaviate
    5. Pinecone
    6. Elasticsearch
    7. OpenSearch

    AI recommended 7 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 completeness
    pass

  • 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 lucasastorian/llmwiki?
    pass
    AI 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?
    pass
    AI 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?
    pass
    AI named lucasastorian/llmwiki explicitly

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

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MARKDOWN (README)
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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