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autoresearch

Automate experimentation loops that mutate prompts and score outputs against binary evals.

Updated Aug 23, 2026
Search Tags:#logs#self-improvement#ai-agent#experimentation#prompt-engineering#autoresearch#binary-evals
One-click install
npx skills add https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit --skill autoresearch-getfresh-ventures
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: autoresearch
Source: https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit/tree/main/skills/autoresearch
Command: npx skills add https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit --skill autoresearch-getfresh-ventures

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates autonomous experimentation loops to optimize Claude Code skills by testing outputs, scoring against binary evals, and mutating prompts to implement improvements.

Core Features & Use Cases

  • Self-improvement pipeline: iteratively mutate prompts and evaluate outputs to strengthen underperforming skills.
  • Benchmarking and logging: automatically generate results logs and a changelog to document improvements over time.
  • Use Case: Continuously improve a skill by running multi-round experiments, selecting mutations that raise the pass rate on binary evals.

Quick Start

Run an autonomous mutation cycle on a target skill and monitor results with a binary eval suite.

Frequently Asked Questions about autoresearch

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate prompt engineering and testing for AI agent skills?▼

Automate prompt engineering by running autonomous experimentation loops that test outputs, score against binary evals, and mutate prompts to iteratively improve underperforming AI agent skills.

What is autonomous iteration for optimizing Claude Code skills?▼

Autonomous iteration applies a single-mutation-per-cycle discipline to test prompt variations, benchmark outputs against binary evals, and generate updated SKILL.md files, results logs, and a changelog.

How do I set up binary evals to benchmark and mutate prompts automatically?▼

Set up binary evals by defining a clear eval suite for your target skill, then run multi-round experiments that select prompt mutations raising the pass rate across multiple test inputs.

Do I need a defined eval suite before starting autonomous experimentation loops?▼

Yes, autonomous experimentation loops require a clearly defined eval suite to score outputs and benchmark prompt mutations effectively across multiple test inputs.

Can I use this autonomous mutation cycle on any skill requiring iterative benchmarking?▼

Yes, the self-improvement pipeline applies to any skill requiring iterative prompt engineering and benchmarking, automatically generating results logs and a changelog to document improvements over time.

What artifacts are generated when running multi-round prompt mutation experiments?▼

Running multi-round mutation experiments generates updated SKILL.md files, results logs documenting test outputs, and a changelog recording each single-mutation-per-cycle improvement.

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