RRepoGEO

REPOGEO REPORT · LITE

kotaro-kinoshita/yomitoku

Default branch main · commit 3d5944ea · scanned 5/20/2026, 2:47:15 PM

GitHub: 1,410 stars · 55 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 kotaro-kinoshita/yomitoku, 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 README's opening to explicitly state 'Python package'

    Why:

    CURRENT
    YomiToku は日本語に特化した AI 文章画像解析エンジン(Document AI)です。
    COPY-PASTE FIX
    YomiToku は日本語に特化した AI 文章画像解析エンジンを提供する Python パッケージです。画像内の文字の全文 OCR およびレイアウト解析機能を有しており、画像内の文字情報や図表を認識、抽出、変換します。
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root, specifying the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumtopics#3
    Expand GitHub Topics with more specific document AI terms

    Why:

    CURRENT
    deep-learning, layout-analysis, ocr, python, pytorch
    COPY-PASTE FIX
    deep-learning, layout-analysis, ocr, python, pytorch, document-ai, document-processing, japanese-ocr, text-extraction, table-extraction

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 kotaro-kinoshita/yomitoku
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ABBYY FineReader Engine
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ABBYY FineReader Engine · recommended 1×
  2. Google Cloud Vision AI · recommended 1×
  3. Amazon Textract · recommended 1×
  4. Microsoft Azure AI Vision · recommended 1×
  5. Tesseract OCR · recommended 1×
  • CATEGORY QUERY
    Need a tool for high-accuracy OCR and layout analysis of Japanese document images.
    you: not recommended
    AI recommended (in order):
    1. ABBYY FineReader Engine
    2. Google Cloud Vision AI
    3. Amazon Textract
    4. Microsoft Azure AI Vision
    5. Tesseract OCR

    AI recommended 5 alternatives but never named kotaro-kinoshita/yomitoku. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Python deep learning libraries for Japanese text and table extraction?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. PyTorch
    4. TensorFlow
    5. OpenCV
    6. PaddleOCR
    7. EasyOCR

    AI recommended 7 alternatives but never named kotaro-kinoshita/yomitoku. 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 kotaro-kinoshita/yomitoku?
    pass
    AI named kotaro-kinoshita/yomitoku explicitly

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

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

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

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kotaro-kinoshita/yomitoku — 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