Github Trends®
9789 findingsmedian surprise 0.00728window 7 days
UNIT / TREND-MONITOR · REV 2.6
[ 7 days window ]
SOURCE: own snapshots
FINDING #5589 · UNIT ID 771350543
Canner/WrenAI
GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.
[ PYTHON ][ ORG ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00297
ENGAGEMENT0.38
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
13.00
ACCEL
-0.25
RETENTION
34.4%
PEAK 2026-09-08 · FORK-RETENTION 50.0% · 91 STARS / WINDOW

Author Audience

AUDIENCE
4,331
FOLLOWERS
256
OWNER ★
19,096

Engagement Signals

FORKS
2,001
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 91 / 91 (DIVERSITY 1.00)

Why This Is A Finding

Canner/WrenAI собрал 91 звёзд за окно, тогда как у автора всего 256 подписчиков — эффективная аудитория ≈ 4,331. Это даёт surprise-индекс 0.00297 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 50.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9789 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 43%
VELOCITY13.003.43+9.57ABOVE 84%
RETENTION34.4%37.5%-3.1 PPABOVE 45%
FORKS2,001120+1,881ABOVE 95%
SURPRISE0.000.01-0.00ABOVE 30%