RRepoGEO

REPOGEO REPORT · LITE

yigitkonur/api-llm-ocr

Default branch main · commit 9b62d14e · scanned 6/14/2026, 5:27:57 PM

GitHub: 894 stars · 60 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 yigitkonur/api-llm-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 README opening to clarify vision LLM and API nature

    Why:

    CURRENT
    LLM-powered PDF to markdown. uses vision models to actually read your documents — tables, headers, mixed layouts — and outputs clean, structured markdown. not traditional OCR.
    COPY-PASTE FIX
    An **API for vision LLM-powered PDF to markdown conversion**. This service uses advanced vision models to *directly read* your documents—preserving tables, headers, and complex layouts—and outputs clean, structured markdown. **This is not traditional OCR combined with an LLM; it leverages vision models end-to-end.**
  • mediumreadme#2
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under the terms specified in the `LICENSE` file. Please refer to that file for full details on usage and distribution.
  • lowhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/yigitkonur/api-llm-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 yigitkonur/api-llm-ocr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Adobe Acrobat Pro DC
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Adobe Acrobat Pro DC · recommended 1×
  2. jgm/pandoc · recommended 1×
  3. pdftotext · recommended 1×
  4. coolwanglu/pdf2htmlEX · recommended 1×
  5. Layout-Parser/layout-parser · recommended 1×
  • CATEGORY QUERY
    Need a tool to convert complex PDF documents into structured markdown, preserving tables and layouts.
    you: not recommended
    AI recommended (in order):
    1. Adobe Acrobat Pro DC
    2. Pandoc (jgm/pandoc)
    3. pdftotext
    4. pdf2htmlEX (coolwanglu/pdf2htmlEX)
    5. LayoutParser (Layout-Parser/layout-parser)
    6. Tesseract (tesseract-ocr/tesseract)
    7. PDFTables.com
    8. Tabula (tabulapdf/tabula)
    9. Aspose.PDF for .NET / Java
    10. Docparser

    AI recommended 10 alternatives but never named yigitkonur/api-llm-ocr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an AI-powered API that extracts structured data from PDFs, understanding context beyond OCR.
    you: not recommended
    AI recommended (in order):
    1. Rossum Aurora
    2. Google Cloud Document AI
    3. Amazon Textract
    4. Microsoft Azure Form Recognizer
    5. Hyperscience
    6. Nanonets

    AI recommended 6 alternatives but never named yigitkonur/api-llm-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 yigitkonur/api-llm-ocr?
    pass
    AI named yigitkonur/api-llm-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 yigitkonur/api-llm-ocr in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yigitkonur/api-llm-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 yigitkonur/api-llm-ocr solve, and who is the primary audience?
    pass
    AI named yigitkonur/api-llm-ocr explicitly

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

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yigitkonur/api-llm-ocr — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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