RRepoGEO

REPOGEO REPORT · LITE

Dicklesworthstone/llm_aided_ocr

Default branch main · commit 9d5d28d4 · scanned 6/24/2026, 6:58:48 PM

GitHub: 2,930 stars · 206 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)

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

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 Dicklesworthstone/llm_aided_ocr, 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 introductory paragraph to clarify its unique application

    Why:

    CURRENT
    The LLM-Aided OCR Project is an advanced system designed to significantly enhance the quality of Optical Character Recognition (OCR) output. By leveraging cutting-edge natural language processing techniques and large language models (LLMs), this project transforms raw OCR text into highly accurate, well-formatted, and readable documents.
    COPY-PASTE FIX
    The LLM-Aided OCR Project is a Python framework that orchestrates Tesseract OCR with Large Language Models (LLMs) to dramatically improve accuracy, correct errors, and format scanned PDFs into clean, structured markdown. It transforms raw OCR text into highly accurate, well-formatted, and readable documents.
  • hightopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    ai-assist, llama2, llm, ocr, ocr-correction, tesseract
    COPY-PASTE FIX
    ai-assist, llama2, llm, ocr, ocr-correction, tesseract, pdf-processing, document-intelligence, ai-application, python-framework, markdown-generation
  • mediumhomepage#3
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/Dicklesworthstone/llm_aided_ocr

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 Dicklesworthstone/llm_aided_ocr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tesseract
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Tesseract · recommended 1×
  2. Pillow (PIL Fork) · recommended 1×
  3. OpenCV · recommended 1×
  4. scikit-image · recommended 1×
  5. ImageMagick · recommended 1×
  • CATEGORY QUERY
    How to improve Tesseract OCR output accuracy and format scanned PDFs using large language models?
    you: not recommended
    AI recommended (in order):
    1. Tesseract
    2. Pillow (PIL Fork)
    3. OpenCV
    4. scikit-image
    5. ImageMagick
    6. OpenAI GPT-4
    7. GPT-3.5 Turbo
    8. Anthropic Claude 3 Opus
    9. Sonnet
    10. Google Gemini Advanced
    11. Hugging Face Transformers
    12. Llama 3
    13. Mistral 7B
    14. ReportLab
    15. PDFMiner.six
    16. PyPDF2

    AI recommended 16 alternatives but never named Dicklesworthstone/llm_aided_ocr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool to correct OCR errors from PDFs and output clean markdown with local AI.
    you: not recommended
    AI recommended (in order):
    1. Nougat (facebookresearch/nougat)
    2. PaddleOCR (PaddlePaddle/PaddleOCR)
    3. Llama 3 (meta-llama/llama3)
    4. Mistral (mistralai/mistral-src)
    5. Gemma (google/gemma.cpp)
    6. Tesseract OCR (tesseract-ocr/tesseract)
    7. DocTR (mindee/doctr)
    8. LayoutParser (Layout-Parser/layout-parser)

    AI recommended 8 alternatives but never named Dicklesworthstone/llm_aided_ocr. 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 Dicklesworthstone/llm_aided_ocr?
    pass
    AI named Dicklesworthstone/llm_aided_ocr explicitly

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

  • If a team adopts Dicklesworthstone/llm_aided_ocr in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Dicklesworthstone/llm_aided_ocr 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 Dicklesworthstone/llm_aided_ocr solve, and who is the primary audience?
    pass
    AI did not name Dicklesworthstone/llm_aided_ocr — 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?

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Dicklesworthstone/llm_aided_ocr — 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