RRepoGEO

REPOGEO REPORT · LITE

remsky/Kokoro-FastAPI

Default branch master · commit 4ecbfe4b · scanned 5/16/2026, 6:27:03 AM

GitHub: 4,844 stars · 807 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 remsky/Kokoro-FastAPI, 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
    Clarify "About" description to emphasize TTS service

    Why:

    CURRENT
    Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model w/CPU ONNX and NVIDIA GPU PyTorch support, handling, and auto-stitching
    COPY-PASTE FIX
    A Dockerized FastAPI service for the Kokoro-82M text-to-speech model, offering multi-language support, an OpenAI-compatible API, and GPU/CPU inference.
  • highhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/Remsky/Kokoro-TTS-Zero
  • mediumreadme#3
    Reposition the README's opening to highlight its role as a complete TTS solution

    Why:

    CURRENT
    Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
    COPY-PASTE FIX
    FastKoko is a complete, Dockerized FastAPI solution for the Kokoro-82M text-to-speech model. It provides an OpenAI-compatible API for multi-language audio generation with GPU/CPU acceleration.

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 remsky/Kokoro-FastAPI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVoice
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVoice · recommended 1×
  2. FastAPI · recommended 1×
  3. Flask · recommended 1×
  4. OpenAI Python library · recommended 1×
  5. XTTS-v2 · recommended 1×
  • CATEGORY QUERY
    How to deploy a multi-language text-to-speech service with an OpenAI-compatible API?
    you: not recommended
    AI recommended (in order):
    1. OpenVoice
    2. FastAPI
    3. Flask
    4. OpenAI Python library
    5. XTTS-v2
    6. Piper
    7. Hugging Face Inference Endpoints
    8. Bark
    9. VALL-E
    10. AWS Polly
    11. Google Cloud Text-to-Speech
    12. Azure Cognitive Services Speech
    13. AWS API Gateway
    14. Lambda
    15. Google Cloud Functions
    16. API Gateway
    17. Azure Functions
    18. API Management

    AI recommended 18 alternatives but never named remsky/Kokoro-FastAPI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Dockerized text-to-speech solution with GPU acceleration for various platforms.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Riva
    2. Coqui TTS
    3. TensorFlow TTS
    4. ESPnet
    5. MaryTTS

    AI recommended 5 alternatives but never named remsky/Kokoro-FastAPI. 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 remsky/Kokoro-FastAPI?
    pass
    AI named remsky/Kokoro-FastAPI explicitly

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

  • If a team adopts remsky/Kokoro-FastAPI in production, what risks or prerequisites should they evaluate first?
    pass
    AI named remsky/Kokoro-FastAPI 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 remsky/Kokoro-FastAPI solve, and who is the primary audience?
    pass
    AI named remsky/Kokoro-FastAPI 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 remsky/Kokoro-FastAPI. 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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  • Brand-free category queries5 vs 2 in Lite
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