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Shanghua-Gao/RSI-Jev

Typed-decision models (noul / choice / score) trained by a self-improving loop of AI agents — checkpoints, the code that produced them, and every version that failed.

Latest metrics (snapshot 2026-10-14)

stars117
forks9
issues0
pushed_at2026-10-10T13:41:32Z

History

History chart: 1 daily snapshot so far (archive started 2026-10-14). The line fills in as the daily archive grows; full series via the API.

DateGitHub stars
2026-10-14117

ADC Momentum: 29/100

ADC Momentum 29 Leaderboard

Growth velocity22
Consistency17
Recency81
Agent demand0
Basisbootstrap

ADC Momentum (0-100) = 45% growth velocity (stars/likes gained per day in our daily archive, relative and absolute, percentile-ranked within the category) + 20% consistency (share of recent days with growth) + 20% recency (latest push/update/release, decaying) + 15% agent demand (how often AI agents looked it up via our API/MCP this week). MCP servers use release cadence; LLMs use price cuts, context and recency. Recomputed daily; scores marked "bootstrap" use lifetime rates until the archive has enough days. Method

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Details

descriptionTyped-decision models (noul / choice / score) trained by a self-improving loop of AI agents — checkpoints, the code that produced them, and every version that failed.
urlhttps://github.com/Shanghua-Gao/RSI-Jev
languageHTML
licenseMIT
topicsai-agents
autonomous-research
decision-model
jev
llm
recursive-self-improvement
system-one
typed-decisions
created_at2026-09-22T10:23:04Z
homepagehttps://shgao.site

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