autoresearch
Category: research-automation · License: MIT · Version: 1.0.0
Tags: Autonomous Research, Two-Loop Architecture, Experiment Orchestration, Research Synthesis, Project Management
When to use it
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.Example requests
Ask your agent in plain language, for example:- “I want to spin up an autonomous research project on whether sparse attention hurts long-context retrieval. Set it up and just start running.”
- “I have a research-state.yaml and findings.md in ~/proj/grokking-wd from last week. Weight decay sweeps on modular addition (H1 supported, H2 inconclusive) and about 12 runs logged in data/trajectory_H1_runs001-012.csv. Pick up where we left off.”
- “I’m going to be offline for a few days. Can you keep investigating why my small transformer’s loss spikes early in training, running experiments on your own, testing ideas, and then writing up what you find with a summary deck I can look at when I’m back?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole research-automation category with /plugin install research-automation@research-agent-skills.