RRepoGEO

REPOGEO REPORT · LITE

minimaxir/gpt-3-experiments

Default branch master · commit d0929d86 · scanned 6/6/2026, 11:52:39 AM

GitHub: 697 stars · 76 forks

AI VISIBILITY SCORE
22 /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
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 minimaxir/gpt-3-experiments, 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 opening to clarify its role as an experimental collection

    Why:

    CURRENT
    A repo containing test prompts for OpenAI's GPT-3 API and the resulting AI-generated texts, which both illustrate the model's robustness, plus a Python script to quickly query texts from the API.
    COPY-PASTE FIX
    A collection of early, unedited experiments and AI-generated texts using OpenAI's GPT-3 API, designed to illustrate the model's diverse capabilities and robustness. This repository also includes a simple Python script for quickly generating texts from the API, primarily for demonstration and exploration rather than systematic testing or production use.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    gpt-3, openai, llm, large-language-models, prompt-engineering, ai-experiments, python, text-generation
  • mediumabout#3
    Enhance the repository description

    Why:

    CURRENT
    Test prompts for OpenAI's GPT-3 API and the resulting AI-generated texts.
    COPY-PASTE FIX
    A collection of early, unedited experiments and AI-generated texts generated using OpenAI's GPT-3 API, demonstrating the model's diverse capabilities and robustness. Includes a Python script for quick text generation.

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 minimaxir/gpt-3-experiments
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Weights & Biases Prompts · recommended 1×
  3. OpenAI Evals · recommended 1×
  4. Humanloop · recommended 1×
  5. PromptLayer · recommended 1×
  • CATEGORY QUERY
    How can I systematically test various prompts and parameters for large language models?
    you: not recommended
    AI recommended (in order):
    1. Weights & Biases Prompts
    2. LangChain
    3. OpenAI Evals
    4. Humanloop
    5. PromptLayer
    6. Guardrails AI
    7. Git

    AI recommended 7 alternatives but never named minimaxir/gpt-3-experiments. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python script to quickly generate diverse texts from a language model API.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Python Library
    2. Hugging Face Transformers
    3. LangChain
    4. LlamaIndex
    5. LiteLLM
    6. Guidance
    7. Instructor

    AI recommended 7 alternatives but never named minimaxir/gpt-3-experiments. 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 minimaxir/gpt-3-experiments?
    pass
    AI did not name minimaxir/gpt-3-experiments — 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 minimaxir/gpt-3-experiments in production, what risks or prerequisites should they evaluate first?
    pass
    AI named minimaxir/gpt-3-experiments 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 minimaxir/gpt-3-experiments solve, and who is the primary audience?
    pass
    AI did not name minimaxir/gpt-3-experiments — 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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minimaxir/gpt-3-experiments — 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