Github Trends®
1069 findingsmedian surprise 0.0527window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: gharchive
FINDING #582 · 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

SURPRISE0.0155
ENGAGEMENT0.20
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
39.00
ACCEL
-25.00
RETENTION
0.0%
PEAK 2026-07-13 · FORK-RETENTION 0.0% · 117 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 117 / 117 (DIVERSITY 1.00)

Why This Is A Finding

teng-lin/notebooklm-py собрал 117 звёзд за окно, тогда как у автора всего 666 подписчиков — эффективная аудитория ≈ 2,478. Это даёт surprise-индекс 0.0155 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 1069 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.01-0.00ABOVE 46%
VELOCITY39.0015.33+23.67ABOVE 76%
RETENTION0.0%33.3%-33.3 PPABOVE 0%
FORKS2,40145+2,356ABOVE 92%
SURPRISE0.020.05-0.04ABOVE 28%