RRepoGEO

REPOGEO REPORT · LITE

Tongyi-Zhiwen/Qwen-Doc

Default branch main · commit 4e5aee32 · scanned 5/31/2026, 10:43:19 PM

GitHub: 535 stars · 24 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 Tongyi-Zhiwen/Qwen-Doc, 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
  • highlicense#1
    Add an Apache-2.0 LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the full text of the Apache-2.0 license.
  • highabout#2
    Populate the repository description in the 'About' section

    Why:

    CURRENT
    Description: (none)
    COPY-PASTE FIX
    An Open-Source Collection of Projects on Document Understanding, Parsing, and Agents, developed by the Tongyi-Zhiwen team.
  • hightopics#3
    Add relevant topics to the repository

    Why:

    CURRENT
    Topics: (none)
    COPY-PASTE FIX
    Add the following topics: "document-ai", "llm", "document-understanding", "document-parsing", "long-context", "ai-agents", "qwen", "benchmark", "multimodal".

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 Tongyi-Zhiwen/Qwen-Doc
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apache Tika
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Apache Tika · recommended 1×
  2. pdfminer/pdfminer.six · recommended 1×
  3. camelot-dev/camelot · recommended 1×
  4. tabulapdf/tabula-py · recommended 1×
  5. ocrmypdf/OCRmyPDF · recommended 1×
  • CATEGORY QUERY
    What open-source tools are available for advanced multi-page document parsing and content extraction?
    you: not recommended
    AI recommended (in order):
    1. Apache Tika
    2. PDFMiner.six (pdfminer/pdfminer.six)
    3. Camelot (camelot-dev/camelot)
    4. Tabula-py (tabulapdf/tabula-py)
    5. OCRmyPDF (ocrmypdf/OCRmyPDF)
    6. Tesseract OCR (tesseract-ocr/tesseract)
    7. DocTR (mindee/doctr)

    AI recommended 7 alternatives but never named Tongyi-Zhiwen/Qwen-Doc. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I leverage AI models to improve long-context understanding and build document-based agents?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Hugging Face Transformers
    5. Hugging Face Datasets
    6. OpenAI API
    7. Anthropic API
    8. Google Gemini API
    9. Weaviate
    10. Pinecone
    11. ChromaDB

    AI recommended 11 alternatives but never named Tongyi-Zhiwen/Qwen-Doc. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Tongyi-Zhiwen/Qwen-Doc?
    pass
    AI named Tongyi-Zhiwen/Qwen-Doc explicitly

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

  • If a team adopts Tongyi-Zhiwen/Qwen-Doc in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Tongyi-Zhiwen/Qwen-Doc 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 Tongyi-Zhiwen/Qwen-Doc solve, and who is the primary audience?
    pass
    AI named Tongyi-Zhiwen/Qwen-Doc 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 Tongyi-Zhiwen/Qwen-Doc. 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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Tongyi-Zhiwen/Qwen-Doc — 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