RRepoGEO

REPOGEO REPORT · LITE

Torantulino/AI-Functions

Default branch master · commit 91393dc4 · scanned 6/15/2026, 2:08:11 PM

GitHub: 936 stars · 106 forks

AI VISIBILITY SCORE
35 /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
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 Torantulino/AI-Functions, 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 clarify its unique value

    Why:

    CURRENT
    # AI Functions 🤖👩‍💻

An easy-to-use implementation of AI functions using OpenAI's GPT-4 (or any other model version) to perform various tasks. This project is heavily inspired by Ask Marvin.
    COPY-PASTE FIX
    # AI-Functions: Generate & Execute Python Functions with LLMs 🤖👩‍💻

AI-Functions empowers developers to define Python function signatures and descriptions, then leverage large language models (LLMs) like GPT-4 to automatically generate and execute their implementations, returning structured data. Inspired by Ask Marvin, it's designed for rapid prototyping and AI-driven code generation.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License.
  • mediumtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    chatgpt, gpt-3, gpt4, openai, openai-api, python
    COPY-PASTE FIX
    ai-functions, llm-functions, code-generation, structured-data, python-library, function-calling, llm-orchestration, prompt-engineering, ai-code-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 Torantulino/AI-Functions
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
spaCy
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. spaCy · recommended 1×
  2. Hugging Face Transformers · recommended 1×
  3. OpenAI API · recommended 1×
  4. NLTK · recommended 1×
  5. Stanford CoreNLP · recommended 1×
  • CATEGORY QUERY
    How can I generate structured data programmatically using natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. Hugging Face Transformers
    3. OpenAI API
    4. NLTK
    5. Stanford CoreNLP
    6. Rasa
    7. Haystack

    AI recommended 7 alternatives but never named Torantulino/AI-Functions. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good libraries for AI-driven function generation in Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain

    AI recommended 1 alternative but never named Torantulino/AI-Functions. 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 Torantulino/AI-Functions?
    pass
    AI named Torantulino/AI-Functions explicitly

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

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

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

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Torantulino/AI-Functions — 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