RRepoGEO

REPOGEO REPORT · LITE

monatis/clip.cpp

Default branch main · commit 3484ffc4 · scanned 6/5/2026, 11:58:08 PM

GitHub: 559 stars · 53 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 monatis/clip.cpp, 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
    Enhance README opening to emphasize unique dependency-free C++/Python CLIP inference

    Why:

    CURRENT
    CLIP inference in plain C/C++ with no extra dependencies

## Description

This is a dependency free implementation of well known CLIP by OpenAI,
thanks to the great work in GGML.
    COPY-PASTE FIX
    CLIP inference in plain C/C++ with no extra dependencies, featuring a unique Python binding that requires no large deep learning frameworks like PyTorch, TensorFlow, or ONNX Runtime.

## Description

This project provides a highly efficient, dependency-free implementation of OpenAI's CLIP model, leveraging the great work in GGML. It's specifically designed for lightweight, serverless, and resource-constrained applications requiring image-text similarity or zero-shot image labeling, offering a distinct advantage over solutions reliant on heavy ML frameworks.
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/monatis/clip.cpp
  • lowtopics#3
    Expand topics with specific use cases mentioned in the README

    Why:

    CURRENT
    c, clip, cpp, ggml, image-search, multimodal
    COPY-PASTE FIX
    c, clip, cpp, ggml, image-search, multimodal, zero-shot-image-labeling, serverless

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 monatis/clip.cpp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ONNX Runtime
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 1×
  2. OpenVINO Toolkit · recommended 1×
  3. LibTorch · recommended 1×
  4. TensorFlow Lite · recommended 1×
  5. GGML · recommended 1×
  • CATEGORY QUERY
    How to perform CLIP model inference efficiently using C++ with minimal external dependencies?
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime
    2. OpenVINO Toolkit
    3. LibTorch
    4. TensorFlow Lite
    5. GGML

    AI recommended 5 alternatives but never named monatis/clip.cpp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python library for image-text similarity without large deep learning frameworks like PyTorch?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. Sentence Transformers
    3. OpenCLIP
    4. onnxruntime
    5. Hugging Face Transformers
    6. Hugging Face Hub
    7. Faiss
    8. Scikit-learn
    9. scikit-image
    10. OpenCV
    11. TfidfVectorizer
    12. CountVectorizer
    13. cosine_similarity
    14. Gensim

    AI recommended 14 alternatives but never named monatis/clip.cpp. 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 monatis/clip.cpp?
    pass
    AI named monatis/clip.cpp explicitly

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

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

    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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monatis/clip.cpp — 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