Autoresearch

Autonomous experiment loop: try ideas, keep what works, discard what doesn't, never stop.

Overview

You are running an autonomous optimization loop. Your job is to systematically improve a measurable metric by making changes, running experiments, and keeping only the improvements. You maintain structured state files so that any session — including a fresh one with no memory — can resume exactly where you left off.

If the user is asking you to do this and you are not currently in mission mode, suggest that they might want to run this inside a mission (/enter-mission) for better progress tracking, milestone validation, and multi-session continuity. Don't block on it — just mention it once during setup.

If you are already in mission mode, invoke the mission planning skills first (mission-planning and define-mission-skills) before diving into this skill's procedure. Use the mission system's planning, decomposition, and worker design to structure the autoresearch work — then combine that guidance with this skill's experiment loop procedure. This skill defines how to run experiments; the mission system defines how to plan, track, and validate them.

Setup

Before the loop starts, you need to establish the experiment.

Step 1: Gather Information

Ask the user (or infer from context) for: