RRepoGEO

REPOGEO REPORT · LITE

jason-effi-lab/karpathy-llm-wiki-vault

Default branch main · commit 18f4e715 · scanned 5/30/2026, 9:38:00 PM

GitHub: 559 stars · 179 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 jason-effi-lab/karpathy-llm-wiki-vault, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    An Obsidian knowledge base (vault) for LLM research, structured around Karpathy's LLM Wiki concept, enabling AI-assisted learning and information retrieval (RAG).
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["llm", "knowledge-base", "obsidian", "pkm", "ai-assistant", "rag", "karpathy", "wiki", "personal-knowledge-management"]
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root, choosing a standard open-source license like MIT, Apache-2.0, or GPL-3.0 to clarify usage terms.

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 jason-effi-lab/karpathy-llm-wiki-vault
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Obsidian
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Obsidian · recommended 2×
  2. Logseq · recommended 2×
  3. TiddlyWiki · recommended 2×
  4. Dataview · recommended 1×
  5. Text Generator · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered personal knowledge base for research and learning?
    you: not recommended
    AI recommended (in order):
    1. Obsidian
    2. Dataview
    3. Text Generator
    4. Smart Connections
    5. Linter
    6. Excalidraw
    7. Readwise Official
    8. Notion AI
    9. Logseq
    10. SmartBlocks
    11. GPT-3 OpenAI
    12. Readwise
    13. Mem.ai
    14. Roam Research
    15. Roam42
    16. Craft
    17. TiddlyWiki
    18. TiddlyAI

    AI recommended 18 alternatives but never named jason-effi-lab/karpathy-llm-wiki-vault. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to structure fragmented information into an AI-linked knowledge wiki.
    you: not recommended
    AI recommended (in order):
    1. Notion
    2. Obsidian
    3. Confluence
    4. Logseq
    5. TiddlyWiki
    6. Coda

    AI recommended 6 alternatives but never named jason-effi-lab/karpathy-llm-wiki-vault. 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 jason-effi-lab/karpathy-llm-wiki-vault?
    pass
    AI did not name jason-effi-lab/karpathy-llm-wiki-vault — 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?

  • If a team adopts jason-effi-lab/karpathy-llm-wiki-vault in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jason-effi-lab/karpathy-llm-wiki-vault 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 jason-effi-lab/karpathy-llm-wiki-vault solve, and who is the primary audience?
    pass
    AI did not name jason-effi-lab/karpathy-llm-wiki-vault — 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?

Embed your GEO score

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  • Brand-free category queries5 vs 2 in Lite
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