RRepoGEO

REPOGEO REPORT · LITE

rust-cv/cv

Default branch main · commit d271a9ac · scanned 5/26/2026, 10:28:06 PM

GitHub: 1,037 stars · 71 forks

AI VISIBILITY SCORE
28 /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
2 / 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 rust-cv/cv, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root, containing the text of your chosen open-source license (e.g., MIT License).
  • highhomepage#2
    Set the repository's homepage URL

    Why:

    COPY-PASTE FIX
    Add the official project website or documentation URL to the repository's 'Homepage' field in GitHub settings.
  • highreadme#3
    Reposition the README's opening paragraph to emphasize 'framework' and `no_std`

    Why:

    CURRENT
    Rust CV is a project to implement computer vision algorithms, abstractions, and systems in Rust. `#[no_std]` is supported where possible.
    COPY-PASTE FIX
    Rust CV is a comprehensive, pure-Rust framework for computer vision algorithms, abstractions, and systems. It offers a cohesive set of APIs, with `#[no_std]` support where possible, making it suitable for both general and embedded computer vision applications.

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 rust-cv/cv
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
image
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. image · recommended 2×
  2. nalgebra · recommended 2×
  3. ndarray · recommended 1×
  4. imageproc · recommended 1×
  5. rust-cv · recommended 1×
  • CATEGORY QUERY
    Seeking a robust pure-Rust framework for computer vision algorithms and image processing applications.
    you: not recommended
    AI recommended (in order):
    1. image
    2. ndarray
    3. nalgebra
    4. imageproc
    5. rust-cv
    6. photon

    AI recommended 6 alternatives but never named rust-cv/cv. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which Rust libraries support `no_std` for embedded computer vision applications?
    you: not recommended
    AI recommended (in order):
    1. image
    2. embedded-graphics
    3. microfft
    4. nalgebra
    5. opencv
    6. opencv-rust
    7. fixed
    8. micromath

    AI recommended 8 alternatives but never named rust-cv/cv. 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 rust-cv/cv?
    pass
    AI did not name rust-cv/cv — 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 rust-cv/cv in production, what risks or prerequisites should they evaluate first?
    pass
    AI named rust-cv/cv 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 rust-cv/cv solve, and who is the primary audience?
    pass
    AI named rust-cv/cv explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite