RRepoGEO

REPOGEO REPORT · LITE

xberg-io/kreuzberg

Default branch main · commit df02ad18 · scanned 6/25/2026, 6:01:53 PM

GitHub: 8,552 stars · 504 forks

AI VISIBILITY SCORE
40 /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
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 xberg-io/kreuzberg, 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
    Add the project's core description to the README

    Why:

    CURRENT
    <p align="center">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://cdn.jsdelivr.net/gh/xberg-io/assets@v1/banner/readme-banner-dark.svg">
    
  </picture>
</p>
    COPY-PASTE FIX
    # Kreuzberg

A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured information from PDFs, Office documents, images, and 97+ formats.
  • mediumreadme#2
    Elaborate on key capabilities and use cases in the README

    Why:

    COPY-PASTE FIX
    ### Key Capabilities

- **Comprehensive Document Parsing:** Extract text, metadata, images, and structured information from PDFs, Office documents (Word, Excel, PowerPoint), images, and 97+ other file formats.
- **RAG Pipeline Integration:** Seamlessly integrate extracted data into Retrieval-Augmented Generation (RAG) pipelines for advanced AI applications.
- **Polyglot Support:** Leverage Kreuzberg's powerful Rust core from a wide array of programming languages.
  • lowreadme#3
    List all supported languages and access methods in the README

    Why:

    COPY-PASTE FIX
    ### Access Kreuzberg

Kreuzberg is available for:
- **Programming Languages:** Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, R, C, TypeScript (Node/Bun/Wasm/Deno)
- **Direct Use:** Via CLI, REST API, or MCP server.

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 xberg-io/kreuzberg
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. Unstructured · recommended 1×
  3. PDFMiner.six · recommended 1×
  4. python-docx · recommended 1×
  5. Tabula-py · recommended 1×
  • CATEGORY QUERY
    How to extract structured data and text from various document types using a single library?
    you: not recommended
    AI recommended (in order):
    1. Apache Tika
    2. Unstructured
    3. PDFMiner.six
    4. python-docx
    5. Tabula-py
    6. PyPDF2
    7. textract

    AI recommended 7 alternatives but never named xberg-io/kreuzberg. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good options for document processing and RAG pipeline integration in Python or Java?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. SpaCy
    5. Hugging Face Transformers
    6. NLTK
    7. Apache Lucene
    8. Elasticsearch
    9. Solr
    10. Deeplearning4j
    11. OpenNLP
    12. Pinecone
    13. Weaviate
    14. Qdrant
    15. Milvus
    16. Chroma
    17. OpenAI API
    18. Anthropic API
    19. Google Cloud Vertex AI
    20. Hugging Face Inference API

    AI recommended 20 alternatives but never named xberg-io/kreuzberg. 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 xberg-io/kreuzberg?
    pass
    AI named xberg-io/kreuzberg explicitly

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

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

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

Embed your GEO score

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xberg-io/kreuzberg — 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