RRepoGEO

REPOGEO REPORT · LITE

openbestof/awesome-ai

Default branch main · commit f6ac5654 · scanned 6/13/2026, 7:18:32 AM

GitHub: 561 stars · 102 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 openbestof/awesome-ai, 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 the README's opening to emphasize its definitive nature for modern AI

    Why:

    CURRENT
    A curated list of awesome AI tools, frameworks, api, software and resources.
    COPY-PASTE FIX
    The definitive curated list of awesome AI tools, frameworks, APIs, software, and resources for modern AI development.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumabout#3
    Update the repository's 'About' description to reinforce its comprehensive and definitive nature

    Why:

    CURRENT
    A curated list of awesome AI tools, frameworks, api, software and resources.
    COPY-PASTE FIX
    The definitive curated list of awesome AI tools, frameworks, APIs, software, and resources for modern AI development.

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 openbestof/awesome-ai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Awesome Lists
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Awesome Lists · recommended 1×
  2. Papers With Code · recommended 1×
  3. Kaggle · recommended 1×
  4. Hugging Face Hub · recommended 1×
  5. Analytics Vidhya · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of modern AI development tools and frameworks?
    you: not recommended
    AI recommended (in order):
    1. GitHub Awesome Lists
    2. Papers With Code
    3. Kaggle
    4. Hugging Face Hub
    5. Analytics Vidhya
    6. Towards Data Science
    7. TensorFlow
    8. PyTorch
    9. scikit-learn

    AI recommended 9 alternatives but never named openbestof/awesome-ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best generative AI models and APIs for building new applications?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Google Cloud Vertex AI
    3. Anthropic Claude
    4. Meta Llama 3
    5. Hugging Face
    6. Mistral AI models
    7. Stable Diffusion
    8. Cohere
    9. Midjourney

    AI recommended 9 alternatives but never named openbestof/awesome-ai. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 openbestof/awesome-ai?
    pass
    AI did not name openbestof/awesome-ai — 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 openbestof/awesome-ai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openbestof/awesome-ai 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 openbestof/awesome-ai solve, and who is the primary audience?
    pass
    AI named openbestof/awesome-ai explicitly

    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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