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ray-r-ren/agent-apprenticeship

The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.

Latest metrics (snapshot 2026-10-14)

stars1617
forks63
issues0
pushed_at2026-10-10T16:16:16Z

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
2026-10-141617

ADC Momentum: 46/100

ADC Momentum 46 Leaderboard

Growth velocity49
Consistency39
Recency82
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

descriptionThe living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.
urlhttps://github.com/ray-r-ren/agent-apprenticeship
languagePython
licenseMIT
topicsagent-apprenticeship
agent-economy
agent-experience
agent-learning
agent-traces
agentic-ai
ai-agents
autonomous-agents
claude-code
codex
cursor
ecosystem-learning
created_at2026-06-19T16:19:37Z
homepagehttps://forsy.ai

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