Autoresearch: Autonomous Improvement Loop

Scan codebase quality metrics, propose improvement loops, and run autonomous agent iterations. Inspired by karpathy/autoresearch, adapted from ML research to code quality.

Concept: The agent proposes a code change, runs the measurement, keeps the change if the metric improved, reverts via git reset if not, and repeats until manually stopped.

Time: Scan ~30s | Per iteration: depends on scope | Loop: runs indefinitely until you stop it

Mode 1: Scan (default)

Measure current state, detect existing loops, propose next actions.

Instructions

Run the following metrics and display a prioritized proposal table.

Step 1: Measure codebase metrics