Autoresearch — Autonomous Goal-directed Iteration

Overview

Autoresearch is a research-focused AI agent skill available within the mxyhi/ok-skills repository. It facilitates an autonomous iteration loop designed to refine outputs based on user-defined metrics. The process involves a continuous cycle of modification and verification, where the agent evaluates changes and decides whether to retain or discard them based on performance against a specific goal. Compatible with agents like Claude-code, Cursor, and OpenClaw, this tool streamlines complex workflows in fields such as security and ROS (Robot Operating System). By leveraging the broader popularity of the mxyhi/ok-skills project, which has garnered 423 stars on GitHub, Autoresearch provides a structured framework for goal-directed experimentation and systematic improvement without requiring manual intervention at every step.

Use Cases

Install Notes

# Review source first
open https://github.com/mxyhi/ok-skills/blob/main/autoresearch/SKILL.md

Copy or clone the skill folder into your agent skills directory after reviewing its instructions and scripts.

Security Notes

As a tool designed for autonomous iteration and verification, users should ensure the agent operates within a sandboxed environment, especially when testing security patches or ROS configurations. Reviewing the specific implementation details in the mxyhi/ok-skills repository is recommended to understand how the skill handles system permissions during the modification and verification cycles.