EverMind-AI/EverOS — GitHub trend

FINDING #989 · UNIT ID 1085086903

EverMind-AI/EverOS

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

[ PYTHON ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.0282

ENGAGEMENT0.20

FRESHNESS1.37

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

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

33% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

121.27

ACCEL

-3.76

RETENTION

33.2%

PEAK 2026-06-28 · FORK-RETENTION 0.0% · 3,638 STARS / WINDOW

Author Audience

AUDIENCE

4,257

FOLLOWERS

471

OWNER ★

16,574

Engagement Signals

FORKS

856

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 3,638 / 3,638 (DIVERSITY 1.00)

Why This Is A Finding

EverMind-AI/EverOS собрал 3,638 звёзд за окно, тогда как у автора всего 471 подписчиков — эффективная аудитория ≈ 4,257. Это даёт surprise-индекс 0.0282 (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.

Related Findings

RANKS ABOVE 84% OF 6295 FINDINGS

#01shy3130/tickflow-stock-panel[ PYTHON ]0.46 #06Panniantong/Agent-Reach[ PYTHON ]0.29 #10sums001/Windows-Copilot-API[ PYTHON ]0.27 #12HUANGCHIHHUNGLeo/claude-real-video[ PYTHON ]0.24 #14realiti4/claude-swap[ PYTHON ]0.21

METRICS IN CONTEXT

MEDIAN ACROSS ALL 6295 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.010.00+0.01ABOVE 84%

VELOCITY121.274.23+117.03ABOVE 98%

RETENTION33.2%29.4%+3.8 PPABOVE 57%

FORKS85692+764ABOVE 91%

SURPRISE0.030.01+0.02ABOVE 74%