autoresearch-agent

Editorial and source context

What this Skill does

Autoresearch Agent is a source-indexed Agent Skill for writing, content & marketing work. Based on the SKILL.md description, it focuses on autonomous experiment loop that optimizes any file by a measurable metric. Use the linked GitHub file to confirm scope and prerequisites before enabling it.

What the author says

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.

Compatibility and requirements

• Use an agent runtime that supports Agent Skills and the linked SKILL.md format.
• Confirm the source repository's tools, SDKs, and platform prerequisites for seo and content work.

How to install or import it

• Open the linked GitHub SKILL.md and review its scope and setup instructions.
• Install or import the skill using the agent runtime's documented workflow.
• Run a small, non-sensitive test and verify the output before broader use.

Permissions and risks

• Review every command, file path, network request, dependency, and credential scope before enabling it.
• GitHub stars indicate popularity, not safety or correctness; validate the source and test with non-sensitive data.

Example workflows

• Ask an AI agent to apply Autoresearch Agent to seo and content work described in the source record.
• Have the agent state assumptions, required tools, and expected output before using this writing, content & marketing skill.
• Compare the result with the linked GitHub SKILL.md and verify it against your project requirements.