RRepoGEO

REPOGEO REPORT · LITE

formulahendry/awesome-gpt

Default branch main · commit 695c8a7a · scanned 5/24/2026, 11:52:14 AM

GitHub: 1,044 stars · 72 forks

AI VISIBILITY SCORE
30 /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
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 formulahendry/awesome-gpt, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    awesome-list, gpt, chatgpt, openai, llm, generative-ai, ai-tools, ai-resources, artificial-intelligence
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Choose an appropriate open-source license like MIT or Apache-2.0 and add it as a LICENSE file in the root of the repository.)
  • mediumreadme#3
    Explicitly state the target audience in the README introduction

    Why:

    CURRENT
    Whether you're just getting started with GPT or you're a seasoned expert, this list has something for everyone.
    COPY-PASTE FIX
    This list is designed for developers, researchers, and enthusiasts looking for practical tools, projects, and resources to leverage GPT, ChatGPT, OpenAI, and other LLMs.

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 formulahendry/awesome-gpt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Hub
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Hub · recommended 1×
  2. GitHub Explore / Trending Repositories · recommended 1×
  3. Papers With Code · recommended 1×
  4. Awesome-LLM · recommended 1×
  5. The Batch by DeepLearning.AI · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of projects using advanced AI language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Hub
    2. GitHub Explore / Trending Repositories
    3. Papers With Code
    4. Awesome-LLM
    5. The Batch by DeepLearning.AI
    6. Towards Data Science
    7. Kaggle

    AI recommended 7 alternatives but never named formulahendry/awesome-gpt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools and resources for building generative AI applications?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Hugging Face Transformers Library (huggingface/transformers)
    3. Google Cloud Vertex AI
    4. LangChain (langchain-ai/langchain)
    5. PyTorch (pytorch/pytorch)
    6. TensorFlow (tensorflow/tensorflow)
    7. Stable Diffusion (Stability-AI/stablediffusion)
    8. Midjourney

    AI recommended 8 alternatives but never named formulahendry/awesome-gpt. 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 formulahendry/awesome-gpt?
    pass
    AI named formulahendry/awesome-gpt explicitly

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

  • If a team adopts formulahendry/awesome-gpt in production, what risks or prerequisites should they evaluate first?
    pass
    AI named formulahendry/awesome-gpt 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 formulahendry/awesome-gpt solve, and who is the primary audience?
    pass
    AI named formulahendry/awesome-gpt explicitly

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

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formulahendry/awesome-gpt — 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