Github Trends®
9558 findingsmedian surprise 0.00429window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #2633 · UNIT ID 872358547
giuseppe99barchetta/SuggestArr
Effortlessly request recommended movies, TV shows and anime to Jellyseer/Overseer based on your recently watched content on Jellyfin, Plex or Emby—let SuggestArr handle it all automatically, keeping your library fresh with new and exciting content!
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0292
ENGAGEMENT0.0927
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
5.67
ACCEL
+4.50
RETENTION
0.0%
PEAK 2026-08-28 · FORK-RETENTION 0.0% · 17 STARS / WINDOW

Author Audience

AUDIENCE
154
FOLLOWERS
18
OWNER ★
1,363

Engagement Signals

FORKS
30
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 17 / 17 (DIVERSITY 1.00)

Why This Is A Finding

giuseppe99barchetta/SuggestArr собрал 17 звёзд за окно, тогда как у автора всего 18 подписчиков — эффективная аудитория ≈ 154. Это даёт surprise-индекс 0.0292 (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.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9558 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00+0.00ABOVE 72%
VELOCITY5.675.670.00ABOVE 49%
RETENTION0.0%42.9%-42.9 PPABOVE 0%
FORKS30333-303ABOVE 14%
SURPRISE0.030.00+0.02ABOVE 81%