RRepoGEO

REPOGEO REPORT · LITE

slavabarkov/tidy

Default branch main · commit eb4aed45 · scanned 6/14/2026, 6:57:28 PM

GitHub: 574 stars · 43 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 slavabarkov/tidy, 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
    Update README H1 to explicitly state Android app nature

    Why:

    CURRENT
    # TIDY - Text-to-Image Discovery
    COPY-PASTE FIX
    # TIDY - Offline Android Text-to-Image Search App
  • mediumhomepage#2
    Add the F-Droid link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://f-droid.org/packages/com.slavabarkov.tidy/
  • mediumtopics#3
    Expand topics with app-specific and on-device AI keywords

    Why:

    CURRENT
    android, clip, computer-vision, cross-modal-retrieval, deep-learning, image-retrieval, image-search, image-text-matching, image-text-retrieval, kotlin, nlp, onnx, quantization, semantic-search
    COPY-PASTE FIX
    android, android-app, clip, computer-vision, cross-modal-retrieval, deep-learning, image-retrieval, image-search, image-text-matching, image-text-retrieval, kotlin, mobile-ai, nlp, offline-search, on-device-ai, onnx, quantization, semantic-search

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 slavabarkov/tidy
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow Lite
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow Lite · recommended 2×
  2. ONNX Runtime · recommended 2×
  3. MobileNetV3 · recommended 1×
  4. EfficientNetLite · recommended 1×
  5. TensorFlow Hub · recommended 1×
  • CATEGORY QUERY
    How to implement offline semantic image search on an Android device?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. MobileNetV3
    3. EfficientNetLite
    4. TensorFlow Hub
    5. TensorFlow Lite Android library
    6. Faiss
    7. JNI
    8. NDK
    9. ONNX
    10. ONNX Runtime
    11. MobileNetV2
    12. EfficientNet
    13. ONNX Runtime Android library
    14. Room Persistence Library
    15. SQLite
    16. K-D Tree
    17. Ball Tree
    18. Hnswlib

    AI recommended 18 alternatives but never named slavabarkov/tidy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a library to perform on-device image-text matching with quantized models.
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. PyTorch Mobile
    3. ONNX Runtime
    4. Core ML
    5. MediaPipe

    AI recommended 5 alternatives but never named slavabarkov/tidy. 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 slavabarkov/tidy?
    pass
    AI named slavabarkov/tidy explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of slavabarkov/tidy. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/slavabarkov/tidy"><img src="https://repogeo.com/badge/slavabarkov/tidy.svg" alt="RepoGEO" /></a>
Pro

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slavabarkov/tidy — 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