RRepoGEO

REPOGEO REPORT · LITE

raghavan/PdfGptIndexer

Default branch main · commit c328dc00 · scanned 6/5/2026, 8:23:11 PM

GitHub: 678 stars · 31 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 raghavan/PdfGptIndexer, 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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    pdf, rag, chatbot, openai, faiss, vector-database, document-qa, llm-application, information-retrieval
  • highreadme#2
    Reposition the README H1 to specify its application category

    Why:

    CURRENT
    # PdfGptIndexer
    COPY-PASTE FIX
    # PdfGptIndexer: A Ready-to-Use AI Chatbot for PDF Document Q&A
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/raghavan/PdfGptIndexer

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 raghavan/PdfGptIndexer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. OpenAI GPT-4 · recommended 1×
  3. GPT-3.5 Turbo · recommended 1×
  4. ChromaDB · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered chatbot for extracting information from multiple PDF files?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI GPT-4
    3. GPT-3.5 Turbo
    4. ChromaDB
    5. Pinecone
    6. LlamaIndex
    7. FAISS
    8. Weaviate
    9. Haystack
    10. Hugging Face Transformers
    11. Elasticsearch
    12. Milvus
    13. Google Cloud Document AI
    14. Vertex AI Conversation
    15. Dialogflow CX
    16. Amazon Textract
    17. Amazon Kendra
    18. Amazon Lex
    19. Amazon Bedrock
    20. PyPDF2
    21. pdfminer.six
    22. scikit-learn
    23. Llama 2
    24. Mistral

    AI recommended 24 alternatives but never named raghavan/PdfGptIndexer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good Python tools for indexing PDF documents with vector embeddings for RAG systems?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (run-llama/llama_index)
    2. LangChain (langchain-ai/langchain)
    3. Haystack (deepset-ai/haystack)
    4. Unstructured (Unstructured-IO/unstructured)
    5. PyMuPDF (pymupdf/PyMuPDF)
    6. pdfminer.six (pdfminer/pdfminer.six)

    AI recommended 6 alternatives but never named raghavan/PdfGptIndexer. 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 raghavan/PdfGptIndexer?
    pass
    AI named raghavan/PdfGptIndexer explicitly

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

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