RRepoGEO

REPOGEO REPORT · LITE

yfedoseev/pdf_oxide

Default branch main · commit 805c94b4 · scanned 5/30/2026, 10:26:30 PM

GitHub: 793 stars · 83 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 yfedoseev/pdf_oxide, 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
    Remove or update 'Work in progress' and 'Not ready for production' statements

    Why:

    COPY-PASTE FIX
    Remove any phrases like 'Work in progress' or 'Not ready for production use' from the README. If the project is stable, replace them with a statement like: 'PDF Oxide is stable and ready for production use, backed by a 100% pass rate on 3,830 real-world PDFs.'
  • highreadme#2
    Strengthen the README's opening paragraph to highlight multi-language speed

    Why:

    CURRENT
    The fastest PDF library for text extraction, image extraction, and markdown conversion. Rust core with bindings for Python, Go, JavaScript / TypeScript, C# / .NET, **Java (JDK 11+, Kotlin-compatible)**, and WASM, plus a CLI tool and MCP server for AI assistants. 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf. 100% pass rate on 3,830 real-world PDFs. MIT licensed.
    COPY-PASTE FIX
    PDF Oxide is the fastest PDF library for text extraction, image extraction, and markdown conversion, built with a Rust core and offering robust bindings for Python, Go, JavaScript/TypeScript, C#/.NET, Java (JDK 11+, Kotlin-compatible), and WASM. Achieve 0.8ms mean processing per document, making it 5× faster than PyMuPDF and 15× faster than pypdf, with a 100% pass rate on 3,830 real-world PDFs. It also includes a CLI tool and MCP server for AI assistants.
  • mediumreadme#3
    Align README license statement with description and actual license

    Why:

    CURRENT
    MIT licensed.
    COPY-PASTE FIX
    Dual-licensed under MIT and Apache-2.0.

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 yfedoseev/pdf_oxide
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
jsvine/pdfplumber
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. jsvine/pdfplumber · recommended 1×
  2. pymupdf/PyMuPDF · recommended 1×
  3. pdfminer/pdfminer.six · recommended 1×
  4. camelot-dev/camelot · recommended 1×
  5. py-pdf/PyPDF2 · recommended 1×
  • CATEGORY QUERY
    What's the fastest Python library for extracting text, images, and converting PDFs to markdown?
    you: not recommended
    AI recommended (in order):
    1. pdfplumber (jsvine/pdfplumber)
    2. PyMuPDF (pymupdf/PyMuPDF)
    3. pdfminer.six (pdfminer/pdfminer.six)
    4. camelot (camelot-dev/camelot)
    5. PyPDF2 (py-pdf/PyPDF2)
    6. unstructured (Unstructured-IO/unstructured)

    AI recommended 6 alternatives but never named yfedoseev/pdf_oxide. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performance, reliable PDF processing toolkit with bindings for Rust or Java.
    you: not recommended
    AI recommended (in order):
    1. Apache PDFBox
    2. QPDF
    3. PDFium
    4. iText
    5. PDF-rs
    6. Poppler

    AI recommended 6 alternatives but never named yfedoseev/pdf_oxide. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 yfedoseev/pdf_oxide?
    pass
    AI named yfedoseev/pdf_oxide explicitly

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

  • If a team adopts yfedoseev/pdf_oxide in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name yfedoseev/pdf_oxide — 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?

  • In one sentence, what problem does the repo yfedoseev/pdf_oxide solve, and who is the primary audience?
    pass
    AI named yfedoseev/pdf_oxide 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 yfedoseev/pdf_oxide. 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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