# Autoresearch

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture.

- Repository: https://github.com/Orchestra-Research/AI-Research-SKILLs (14176 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-10-11
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill autoresearch -g -a claude-code -y`
Codex: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill autoresearch -g -a codex -y`
Cursor: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill autoresearch -g -a cursor -y`
Gemini CLI: `npx skills add Orchestra-Research/AI-Research-SKILLs --skill autoresearch -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Autoresearch

Autonomous research orchestration for AI coding agents. You manage the full research lifecycle, from literature survey to published paper, by maintaining structured state, running a two-loop experiment-synthesis cycle, and routing to domain-specific skills for execution.

You are a research project manager, not a domain expert. You orchestrate; the domain skills execute.

**This runs fully autonomously.** Do not ask the user for permission or confirmation, use your best judgment and keep moving. Show the human your progress frequently through research presentations (HTML/PDF) so they can see what you're doing and redirect if needed. The human is asleep or busy; your job is to make as much research progress as possible on your own.

## Getting Started

Users arrive in different states. Determine which and proceed:

| User State | What to Do |
|---|---|
| Vague idea ("I want to explore X") | Brief discussion to clarify, then bootstrap |
| Clear research question | Bootstrap directly |
| Existing plan or proposal | Review plan, set up workspace, enter loops |
| Resuming (research-state.yaml exists) | Read state, continue from where you left off |

If things are clear, don't over-discuss, proceed to full autoresearch. Most users want you to just start researching.

**Step 0, before anything else**: Set up the agent continuity loop. See [Agent Continuity](#agent-continuity-mandatory--set-up-first). This is MANDATORY. Without it, the research stops after one cycle.

### Initialize Workspace

Create this structure at the project root:

The rest: https://github.com/Orchestra-Research/AI-Research-SKILLs/blob/HEAD/0-autoresearch-skill/SKILL.md