Autoresearch
brycewang-stanford/Auto-Empirical-Research-SkillsOrchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
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/plugin marketplace add brycewang-stanford/Auto-Empirical-Research-Skills
/plugin install autoresearch
Setup, runtime and requirements describe brycewang-stanford/Auto-Empirical-Research-Skills, the repo this skill ships in.
Also in brycewang-stanford/Auto-Empirical-Research-Skills
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Create academic presentations in Beamer with professional themes
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