Github Trends®
1013 findingsmedian surprise 0.0334window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: gharchive
FINDING #393 · UNIT ID 1129786550
teng-lin/notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0178
ENGAGEMENT0.20
FRESHNESS1.39
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
8% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
44.77
ACCEL
+0.63
RETENTION
41.5%
PEAK 2026-07-08 · FORK-RETENTION 0.0% · 1,343 STARS / WINDOW

Author Audience

AUDIENCE
2,478
FOLLOWERS
666
OWNER ★
18,122

Engagement Signals

FORKS
2,401
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 1,343 / 1,343 (DIVERSITY 1.00)

Why This Is A Finding

teng-lin/notebooklm-py собрал 1,343 звёзд за окно, тогда как у автора всего 666 подписчиков — эффективная аудитория ≈ 2,478. Это даёт surprise-индекс 0.0178 (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 1013 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.00+0.00ABOVE 61%
VELOCITY44.777.20+37.57ABOVE 83%
RETENTION41.5%30.8%+10.7 PPABOVE 68%
FORKS2,40156+2,345ABOVE 93%
SURPRISE0.020.03-0.02ABOVE 34%