leo-lilinxiao/codex-autoresearch

Health v2 · maintenance only

Flags: young

Adoption not part of the score

2255 stars · 125 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Codex skill that runs a self-directed iterative loop: it makes one focused change, measures it against a target metric, keeps improvements, reverts failures, and repeats until the goal is reached. Inspired by Karpathy's autoresearch concept, it supports foreground and background runs with commit, verification, and rollback handled by a control script.

Use cases

• automatically reduce test failures to zero
• iteratively improve code coverage until a target
• fix type errors and compiler warnings autonomously
• optimize latency or binary size with an agent loop
• run overnight autonomous experiments on a repository
• keep-and-revert agent-driven code changes based on measurable results

When to choose

• you have a measurable target metric a command can evaluate
• you want autonomous, auditable iteration with automatic rollback of failed changes
• you already use OpenAI Codex CLI and want a skill-based workflow

When to avoid

• your goal is subjective and cannot be measured by a command
• you don't use Codex or another compatible agent CLI
• you can't grant the broad permissions the loop needs to commit and revert code

Facets

plugin · maturity active

agent-framework workflow-automation developer-tools testing developer-tools large-language-models cli python cross-platform codex-skill autonomous-iteration autoresearch openai-codex self-directed-loop experiment-automation git-rollback automation ai-agents

Member repositories

For agents

markdown · JSON · MCP: product_card(name="leo-lilinxiao/codex-autoresearch")