Github Trends®
8356 findingsmedian surprise 0.00472window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #228 · UNIT ID 1394675848
Akun-python/autumn-recruitment
Autumn recruitment preparation for algorithm position. Contains categorized LeetCode solutions, enterprise written exam codes, interview experience and CS fundamentals notes including CN, OS and DB.
[ JUPYTER NOTEBOOK ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.17
ENGAGEMENT0.47
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
22% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
13.67
ACCEL
-2.00
RETENTION
70.6%
PEAK 2026-10-05 · FORK-RETENTION 28.6% · 41 STARS / WINDOW

Author Audience

AUDIENCE
42
FOLLOWERS
11
OWNER ★
321

Engagement Signals

FORKS
24
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 41 / 41 (DIVERSITY 1.00)

Why This Is A Finding

Akun-python/autumn-recruitment собрал 41 звёзд за окно, тогда как у автора всего 11 подписчиков — эффективная аудитория ≈ 42. Это даёт surprise-индекс 0.17 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 28.6% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 8356 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.100.00+0.10ABOVE 97%
VELOCITY13.675.67+8.00ABOVE 77%
RETENTION70.6%40.0%+30.6 PPABOVE 75%
FORKS24320-295ABOVE 13%
SURPRISE0.170.00+0.16ABOVE 96%