Github Trends®
9595 findingsmedian surprise 0.00815window 30 days
UNIT / TREND-MONITOR · REV 2.6
[ 30 days window ]
SOURCE: own snapshots
FINDING #7519 · UNIT ID 1291994110
TingxiYu/academic-figure-skill
A skill for academic research figure generation that autonomously handles the full workflow — data understanding, chart type recommendation, and format-compliant generation.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0403
ENGAGEMENT0.28
FRESHNESS1.38
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
43% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S7 · THIS REPO IS ~ALL OF THE OWNER'S STARS
S10 · DEAD CODE, ZERO CONTRIBUTORS, YET STARS KEEP DRIPPING

Growth Telemetry

VELOCITY /D
4.27
ACCEL
+0.13
RETENTION
66.7%
PEAK 2026-08-23 · FORK-RETENTION 33.3% · 128 STARS / WINDOW

Author Audience

AUDIENCE
66
FOLLOWERS
36
OWNER ★
299

Engagement Signals

FORKS
15
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 128 / 128 (DIVERSITY 1.00)

Why This Is A Finding

TingxiYu/academic-figure-skill собрал 128 звёзд за окно, тогда как у автора всего 36 подписчиков — эффективная аудитория ≈ 66. Это даёт surprise-индекс 0.0403 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 33.3% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9595 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 22%
VELOCITY4.273.67+0.60ABOVE 56%
RETENTION66.7%24.6%+42.0 PPABOVE 98%
FORKS15115-100ABOVE 12%
SURPRISE0.040.01+0.03ABOVE 88%