RRepoGEO

REPOGEO REPORT · LITE

yurijmikhalevich/rclip

Default branch main · commit bd937bf1 · scanned 6/9/2026, 4:32:16 AM

GitHub: 939 stars · 71 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 yurijmikhalevich/rclip, 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 paragraph to emphasize its unique CLI and local nature

    Why:

    CURRENT
    **rclip** is a command-line semantic photo search tool powered by OpenCLIP's top-performing ViT-B/32 model. Search a local photo library with natural-language queries, similar image search, or mixed text and image queries directly from the terminal. It builds on the CLIP architecture introduced by OpenAI.
    COPY-PASTE FIX
    **rclip** is a powerful, AI-powered command-line utility designed for semantic photo search within your *local* photo library. It allows you to find images using natural-language queries, similar image examples, or a combination of both, all directly from your terminal. Built on OpenCLIP's ViT-B/32 model, rclip brings advanced AI search capabilities to your desktop, without needing cloud services.
  • hightopics#2
    Add more specific topics to clarify the tool's scope

    Why:

    CURRENT
    artificial-intelligence, computer-vision, hacktoberfest, image-search, photo-search, photography, python, semantic-image-search
    COPY-PASTE FIX
    artificial-intelligence, computer-vision, image-search, photo-search, photography, python, semantic-image-search, cli-tool, local-search, offline-search, desktop-utility
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://mikhalevi.ch/rclip-an-ai-powered-command-line-photo-search-tool/

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 yurijmikhalevich/rclip
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
img2dataset
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. img2dataset · recommended 1×
  2. CLIP-as-service · recommended 1×
  3. Jina AI · recommended 1×
  4. Faiss · recommended 1×
  5. Elasticsearch · recommended 1×
  • CATEGORY QUERY
    Need a command-line utility for AI-powered image search with text queries.
    you: not recommended
    AI recommended (in order):
    1. img2dataset
    2. CLIP-as-service
    3. Jina AI
    4. Faiss
    5. Elasticsearch

    AI recommended 5 alternatives but never named yurijmikhalevich/rclip. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some Python CLI tools for semantic photo search in a local library?
    you: not recommended
    AI recommended (in order):
    1. imgsearch (imgsearch/imgsearch)
    2. PhotoPrism (photoprism/photoprism)
    3. LlamaIndex (run-llama/llama_index)
    4. Ollama (ollama/ollama)
    5. transformers (huggingface/transformers)
    6. Faiss (facebookresearch/faiss)
    7. OpenCLIP (mlfoundations/open_clip)
    8. Elasticsearch (elastic/elasticsearch)
    9. elasticsearch-py (elastic/elasticsearch-py)
    10. Pimcore (pimcore/pimcore)

    AI recommended 10 alternatives but never named yurijmikhalevich/rclip. 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 yurijmikhalevich/rclip?
    pass
    AI named yurijmikhalevich/rclip explicitly

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

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

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

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MARKDOWN (README)
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yurijmikhalevich/rclip — 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