AI & Machine Learning

Autoresearch

Orchestrates 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.

Publisher / source
KalarisLabs/research-agent-skills (found on the CSV list)
Upstream record
KalarisLabs/research-agent-skills
Version
Version 2
Published
Publication review
Approved for publication
Content fingerprint
bfa97577c399d43a7b8d066d2a11e479d7bb8f02a3472a4e333519d8134ce25e