RRepoGEO

REPOGEO REPORT · LITE

slavingia/askmybook

Default branch main · commit f356ae9c · scanned 6/6/2026, 4:47:56 PM

GitHub: 506 stars · 182 forks

AI VISIBILITY SCORE
23 /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
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 slavingia/askmybook, 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
  • highabout#1
    Add a concise 'About' description for the repository

    Why:

    COPY-PASTE FIX
    A Python web application that allows users to ask natural language questions to a PDF book and receive AI-generated answers, built with Django, LangChain, and OpenAI.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    python, django, langchain, openai, pdf, q-and-a, embeddings, ai, generative-ai, web-app
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root and populate it with the text of the MIT License.

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 slavingia/askmybook
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Pinecone · recommended 2×
  3. OpenAI's GPT-4 · recommended 2×
  4. Streamlit · recommended 2×
  5. Gradio · recommended 2×
  • CATEGORY QUERY
    How can I create an AI-powered Q&A interface for a PDF book?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI
    3. Anthropic
    4. Google Gemini
    5. Chroma
    6. Pinecone
    7. PyPDF2
    8. pdfminer.six
    9. Adobe PDF Extract API
    10. Google Cloud Document AI
    11. OpenAI's `text-embedding-ada-002`
    12. Cohere Embed
    13. Google's `text-embedding-004`
    14. OpenAI's GPT-4
    15. Anthropic's Claude 3
    16. Google's Gemini Pro
    17. Streamlit
    18. Gradio
    19. React
    20. Vue.js
    21. Flask
    22. FastAPI
    23. LlamaIndex
    24. FAISS
    25. Weaviate
    26. Qdrant
    27. OpenAI's GPT-3.5 Turbo
    28. Anthropic's Claude 3 Haiku
    29. Haystack
    30. Hugging Face Models
    31. Elasticsearch
    32. OpenSearch
    33. Hugging Face Transformers
    34. `sentence-transformers/all-MiniLM-L6-v2`
    35. BERT
    36. RoBERTa
    37. Flan-T5
    38. Mistral 7B
    39. OpenAI Assistants API
    40. GPT-4 Turbo
    41. `transformers`
    42. `faiss-cpu`
    43. NLTK
    44. spaCy
    45. `sentence-transformers`
    46. OpenAI API
    47. Anthropic API

    AI recommended 47 alternatives but never named slavingia/askmybook. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python project to build a web app answering questions from documents.
    you: not recommended
    AI recommended (in order):
    1. Streamlit
    2. LangChain
    3. LlamaIndex
    4. FAISS
    5. ChromaDB
    6. Pinecone
    7. OpenAI's GPT-4
    8. Anthropic's Claude
    9. Hugging Face
    10. Gradio
    11. FastAPI
    12. React
    13. Vue
    14. Flask
    15. Django
    16. Jinja2
    17. Panel
    18. HoloViz
    19. Pandas
    20. NumPy
    21. Bokeh

    AI recommended 21 alternatives but never named slavingia/askmybook. 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 slavingia/askmybook?
    pass
    AI did not name slavingia/askmybook — 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?

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite