Claude Autoresearch Skill — Autonomous goal-directed iteration for Claude Code. Inspired by Karpathy's autoresearch. Modify → Verify → Keep/Discard → Repeat forever.

A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Karpathy's autoresearch.

The first distributed AGI system. Thousands of autonomous AI agents collaboratively train models, share experiments via P2P gossip, and push breakthroughs here. Fully peer-to-peer. Join from your browser or CLI.

Codex Autoresearch Skill — A self-directed iterative system for Codex that continuously cycles through: modify, verify, retain or discard, and repeat indefinitely. Inspired by Karpathy’s autoresearch concept.

🦞+🔬 NanoResearch: The Autonomous AI Research Assistant

Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.

AIDE: AI-Driven Exploration in the Space of Code. The machine Learning engineering agent that automates AI R&D.

a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

Curated list of AutoResearch use cases with optimization traces and open source implementations

CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch. Works with Claude Code, Codex, Cursor, OpenCode, Kiro, and more.

A codex plugin for running optimization loops inside a codebase. It is useful when you have a measurable target and many possible changes to try: test runtime, build speed, bundle size, model loss, Lighthouse scores, memory use, query latency, or any other metric you can print from a script.

Scholar All-In-One: A research infrastructure for AI agents

800+ pure-markdown skills for autonomous AI research. Non-linear orchestration with backtracking, 4-layer military hierarchy (Campaign → Strategy → Tactic → SOP), 5 MCP integrations. The AI is the researcher — you set the direction.

Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code

One file. Your AI coding agent becomes a scientist. 30+ experiments while you sleep.

Autoresearch for LLM adversarial attacks

Autonomous Qwen3-VL training-code research on the official DocVQA benchmark. main: NVIDIA multi-GPU, mlx: Apple Silicon/MPS.

A self-improving loop for voice AI agents. Uses karpathy's autoresearch as foundation.

A curated list of awesome autonomous researcher frameworks