RRepoGEO

REPOGEO REPORT · LITE

hayabhay/frogbase

Default branch main · commit ba41845e · scanned 5/31/2026, 10:08:03 AM

GitHub: 776 stars · 91 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 hayabhay/frogbase, 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
    Clarify the project's identity in the README's opening

    Why:

    CURRENT
    # 🐸 FrogBase
> _**Create navigable knowledge from multi-media content**_
    COPY-PASTE FIX
    # 🐸 FrogBase: A Python Library & UI for Creating Navigable Knowledge from Multimedia Content
  • mediumabout#2
    Expand the repository description with key functionalities

    Why:

    CURRENT
    Transform audio-visual content into navigable knowledge.
    COPY-PASTE FIX
    Transform audio-visual content (videos, podcasts) into searchable, navigable knowledge bases using speech-to-text, embeddings, and a Streamlit UI.
  • mediumtopics#3
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    embeddings, package, python, search, semantic-search, speech-to-text, streamlit, ui
    COPY-PASTE FIX
    multimedia, knowledge-base, video-analysis, audio-analysis, transcription, semantic-search, embeddings, speech-to-text, streamlit, python, ui, yt-dlp, whisper

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 hayabhay/frogbase
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AssemblyAI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AssemblyAI · recommended 1×
  2. Elasticsearch · recommended 1×
  3. React · recommended 1×
  4. Vue · recommended 1×
  5. Angular · recommended 1×
  • CATEGORY QUERY
    How to create a searchable knowledge base from video and audio files?
    you: not recommended
    AI recommended (in order):
    1. AssemblyAI
    2. Elasticsearch
    3. React
    4. Vue
    5. Angular
    6. Deepgram
    7. Pinecone
    8. AWS MediaConvert
    9. AWS Transcribe
    10. AWS OpenSearch Service
    11. AWS Amplify
    12. S3
    13. AWS Lambda
    14. Google Cloud Video AI
    15. Google Cloud Speech-to-Text
    16. Google Cloud Search
    17. Otter.ai
    18. Trint
    19. Veed.io

    AI recommended 19 alternatives but never named hayabhay/frogbase. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python library with a user interface for transcribing and semantically searching multimedia?
    you: not recommended
    AI recommended (in order):
    1. WhisperX
    2. Streamlit
    3. Gradio
    4. Sentence-Transformers
    5. OpenAI's embeddings
    6. ChromaDB
    7. FAISS
    8. AssemblyAI Python SDK
    9. PyDub
    10. SpeechRecognition
    11. Google Web Speech API
    12. CMU Sphinx
    13. DeepSpeech (Mozilla)
    14. MoviePy

    AI recommended 14 alternatives but never named hayabhay/frogbase. 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 hayabhay/frogbase?
    pass
    AI named hayabhay/frogbase explicitly

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

  • If a team adopts hayabhay/frogbase in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hayabhay/frogbase 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 hayabhay/frogbase solve, and who is the primary audience?
    pass
    AI named hayabhay/frogbase 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 hayabhay/frogbase. 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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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite