RRepoGEO

REPOGEO REPORT · LITE

NeptuneHub/AudioMuse-AI

Default branch main · commit 6b61436e · scanned 5/17/2026, 1:47:21 AM

GitHub: 1,739 stars · 99 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)

2 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 NeptuneHub/AudioMuse-AI, 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 the README H1 and opening paragraph to clarify its role as a media server enhancement

    Why:

    CURRENT
    # **AudioMuse-AI - Where Music Takes Shape** 

<p align="center">
  
</p>

AudioMuse-AI is an open-source, Dockerized environment that brings **automatic playlist generation** to your self-hosted music library. Using tools such as Librosa and ONNX, it performs **sonic analysis** on your audio files locally, allowing you to curate playlists for any mood or occasion without relying on external APIs.
    COPY-PASTE FIX
    # **AudioMuse-AI: The Smart Playlist Engine for Your Self-Hosted Music Servers** 

AudioMuse-AI is an open-source, Dockerized environment that acts as a powerful **automatic playlist generator** for your self-hosted music library. It enhances media servers like Jellyfin, Navidrome, LMS, Lyrion, and Emby by performing **sonic analysis** on your audio files locally, allowing you to curate playlists for any mood or occasion without relying on external APIs or existing metadata.
  • mediumtopics#2
    Add more specific topics to emphasize its function and role

    Why:

    CURRENT
    clap, docker, emby, jellyfin, jellyfin-plugin, k3s, kubernetes, librosa, llm, lyrion, music, navidrome, ollama, onnx, open-source, open-source-project, playlist, self-hosted, smart-playlists, sonic-analysis
    COPY-PASTE FIX
    clap, docker, emby, jellyfin, jellyfin-plugin, k3s, kubernetes, librosa, llm, lyrion, music, navidrome, ollama, onnx, open-source, open-source-project, playlist, self-hosted, smart-playlists, sonic-analysis, music-recommendation, playlist-generator, audio-analysis-engine, media-server-enhancement
  • mediumabout#3
    Refine the 'About' description to emphasize its role as an enhancement engine

    Why:

    CURRENT
    AudioMuse-AI is a self-hosted, Dockerized music playlist generator using sonic analysis to discover related tracks for Jellyfin, Navidrome, LMS, Lyrion, and Emby: no metadata or external APIs needed.
    COPY-PASTE FIX
    AudioMuse-AI is a self-hosted, Dockerized smart playlist engine that enhances Jellyfin, Navidrome, LMS, Lyrion, and Emby by generating music playlists using local sonic analysis, requiring no metadata or external APIs.

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 NeptuneHub/AudioMuse-AI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MusicBrainz Picard
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. MusicBrainz Picard · recommended 1×
  2. foobar2000 · recommended 1×
  3. beaTunes · recommended 1×
  4. Lexicon · recommended 1×
  5. MediaMonkey · recommended 1×
  • CATEGORY QUERY
    How to generate music playlists automatically from local files using audio analysis?
    you: not recommended
    AI recommended (in order):
    1. MusicBrainz Picard
    2. foobar2000
    3. beaTunes
    4. Lexicon
    5. MediaMonkey
    6. Jaikoz Audio Tagger
    7. MP3Tag

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

    Show full AI answer
  • CATEGORY QUERY
    Looking for a self-hosted solution to create smart music playlists based on audio characteristics.
    you: not recommended
    AI recommended (in order):
    1. Jellyfin
    2. Navidrome
    3. Funkwhale
    4. Plex
    5. Plexamp
    6. Kodi

    AI recommended 6 alternatives but never named NeptuneHub/AudioMuse-AI. 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 NeptuneHub/AudioMuse-AI?
    pass
    AI named NeptuneHub/AudioMuse-AI explicitly

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

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

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

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NeptuneHub/AudioMuse-AI — 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