NeptuneHub/AudioMuse-AI — GitHub trend

FINDING #3850 · UNIT ID 989499651

NeptuneHub/AudioMuse-AI

AudioMuse-AI uses sonic analysis to rediscover forgotten songs, uncover hidden connections in your music library, and generate intelligent playlists for Navidrome, Jellyfin, LMS, Lyrion, Emby and Plex: no metadata or external services required.

[ PYTHON ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.0104

ENGAGEMENT0.24

FRESHNESS1.00

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

1% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

5.29

ACCEL

+0.07

RETENTION

0.0%

PEAK 2026-08-29 · FORK-RETENTION 0.0% · 37 STARS / WINDOW

Author Audience

AUDIENCE

469

FOLLOWERS

149

OWNER ★

3,210

Engagement Signals

FORKS

145

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 37 / 37 (DIVERSITY 1.00)

Why This Is A Finding

NeptuneHub/AudioMuse-AI собрал 37 звёзд за окно, тогда как у автора всего 149 подписчиков — эффективная аудитория ≈ 469. Это даёт surprise-индекс 0.0104 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

Related Findings

RANKS ABOVE 61% OF 9771 FINDINGS

#05MddIdd/mdd-sim-gateway[ PYTHON ]0.41 #08zeenie-ai/OpenCompany[ PYTHON ]0.38 #15litaolemo/xtquant_big_convert[ PYTHON ]0.33 #23917Dhj/DeepPaperNote[ PYTHON ]0.27 #24LBH-123-AI/Comfyui_Minimax_h3_latent_Upscaler[ PYTHON ]0.27

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9771 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00+0.00ABOVE 61%

VELOCITY5.293.71+1.57ABOVE 62%

RETENTION0.0%39.3%-39.3 PPABOVE 0%

FORKS14591+54ABOVE 61%

SURPRISE0.010.01+0.00ABOVE 53%