RRepoGEO

REPOGEO REPORT · LITE

moonshine-ai/moonshine

Default branch main · commit 16d5b520 · scanned 6/25/2026, 10:51:45 PM

GitHub: 8,542 stars · 463 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 moonshine-ai/moonshine, 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
    Reposition README's opening to explicitly state "voice" and "audio" focus

    Why:

    CURRENT
    Moonshine Voice is an open source AI toolkit for developers building real-time voice agents and applications.
    COPY-PASTE FIX
    Moonshine Voice is an open-source AI toolkit specifically designed for developers building real-time *audio-first* voice agents and applications, focusing on speech-to-text, intent recognition, and text-to-speech.
  • mediumtopics#2
    Expand topics with more specific voice/audio processing terms

    Why:

    CURRENT
    intent-recognition, stt, tts, voice, voice-recognition
    COPY-PASTE FIX
    intent-recognition, stt, tts, voice, voice-recognition, speech-recognition, audio-processing, real-time-audio, on-device-ai, edge-ai, conversational-ai, voice-ai
  • mediumlicense#3
    Add a clear statement about the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under [Specific License Name(s), e.g., a custom license combining X and Y]. Please see the [LICENSE file](LICENSE) for full details.

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 moonshine-ai/moonshine
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mozilla DeepSpeech
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mozilla DeepSpeech · recommended 2×
  2. Vosk · recommended 2×
  3. Edge Impulse · recommended 2×
  4. Picovoice Rhino Speech-to-Intent & Porcupine Wake Word · recommended 1×
  5. Apple Speech Framework · recommended 1×
  • CATEGORY QUERY
    What are the best on-device tools for real-time low-latency speech-to-text and voice agents?
    you: not recommended
    AI recommended (in order):
    1. Picovoice Rhino Speech-to-Intent & Porcupine Wake Word
    2. Mozilla DeepSpeech
    3. Apple Speech Framework
    4. Google Speech Recognizer
    5. Vosk
    6. Edge Impulse
    7. TensorFlow Lite for Microcontrollers

    AI recommended 7 alternatives but never named moonshine-ai/moonshine. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an alternative to Whisper for highly accurate, private, cross-platform voice interface development.
    you: not recommended
    AI recommended (in order):
    1. Picovoice Rhino Speech-to-Intent
    2. Porcupine Wake Word
    3. Leopard Speech-to-Text
    4. Mozilla DeepSpeech
    5. Coqui STT
    6. Vosk
    7. Speechly
    8. Edge Impulse
    9. Google ML Kit
    10. Android SpeechRecognizer API

    AI recommended 10 alternatives but never named moonshine-ai/moonshine. 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 moonshine-ai/moonshine?
    pass
    AI named moonshine-ai/moonshine explicitly

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

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

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

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MARKDOWN (README)
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moonshine-ai/moonshine — 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