neo4j-labs/agent-memory — GitHub trend

FINDING #6900 · UNIT ID 1129311820

neo4j-labs/agent-memory

A graph-native memory system for AI agents and context graphs. Store conversations, build knowledge graphs, and let your agents learn from their own reasoning — all backed by Neo4j.

[ PYTHON ][ ORG ][ VERIFIED ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.00129

ENGAGEMENT0.32

FRESHNESS1.00

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

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

5% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

3.86

ACCEL

-0.21

RETENTION

35.0%

PEAK 2026-08-25 · FORK-RETENTION 0.0% · 27 STARS / WINDOW

Author Audience

AUDIENCE

2,960

FOLLOWERS

347

OWNER ★

9,130

Engagement Signals

FORKS

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 27 / 27 (DIVERSITY 1.00)

Why This Is A Finding

neo4j-labs/agent-memory собрал 27 звёзд за окно, тогда как у автора всего 347 подписчиков — эффективная аудитория ≈ 2,960. Это даёт surprise-индекс 0.00129 (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 29% OF 9755 FINDINGS

#01wang2122/sprix-sage-router[ PYTHON ]0.81 #07MddIdd/mdd-sim-gateway[ PYTHON ]0.43 #10zeenie-ai/OpenCompany[ PYTHON ]0.39 #15HRuiCcc/music-geshizhuanhuan[ PYTHON ]0.32 #16litaolemo/xtquant_big_convert[ PYTHON ]0.32

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9755 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00-0.00ABOVE 29%

VELOCITY3.863.71+0.14ABOVE 51%

RETENTION35.0%37.5%-2.5 PPABOVE 47%

FORKS9790+7ABOVE 52%

SURPRISE0.000.01-0.01ABOVE 16%