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ck:autoresearch

Iteratively adjust code or configuration to improve measurable metrics with Git rollback.

1|1|Updated Jan 15, 2026
Search Tags:#performance optimization#iterative improvement#autonomous optimization#metrics improvement#code adjustment
One-click install
npx skills add https://github.com/Thanh-apero/apero-kit-cli --skill ck-autoresearch-thanh-apero
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ck:autoresearch
Source: https://github.com/Thanh-apero/apero-kit-cli/tree/main/.claude/skills/ck-autoresearch
Command: npx skills add https://github.com/Thanh-apero/apero-kit-cli --skill ck-autoresearch-thanh-apero

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The ck:autoresearch Skill solves the problem of iterative optimization for measurable metrics, allowing users to improve performance metrics through automated experimentation.

Core Features & Use Cases

  • Automated Optimization: Iteratively adjusts code or configuration to improve specific metrics such as test coverage, performance, or bundle size.
  • Git-Tracking: Supports Git for rollback capabilities and tracks changes through a series of commits.
  • Customizable Configuration: Users can define their own goal, scope, and verification command for targeted improvements.

Quick Start

Use the ck:autoresearch command with the following parameters:

Goal: "Improve performance metric in src/app.ts"
Scope: "src/app.ts"
Verify: "node performance_test.js"
Guard: "npm test"

Frequently Asked Questions about ck:autoresearch

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

FAQPage Schema
How do I automate performance optimization for specific code files?▼

Automate performance optimization by iteratively adjusting code or configuration to improve specific metrics. You define a target goal, scope, and verification command, enabling the system to autonomously experiment and measure improvements.

How does autonomous iterative improvement handle rollback when code adjustments fail?▼

Autonomous iterative improvement handles rollback by tracking changes through a series of Git commits. This provides regression risk management and allows reverting adjustments if verification commands fail.

Can I use autonomous optimization to increase test coverage and validate changes?▼

Yes, you can use autonomous optimization to increase test coverage by defining it as your goal. You set a verification command to validate coverage and a guard command to ensure existing tests pass during code adjustment.

What is the best way to configure code adjustment for bundle size reduction?▼

The best way to configure bundle size reduction is to specify the goal, target scope, a verification command to measure size, and a guard command to prevent regressions, allowing automated experimentation to find optimal adjustments.

Do I need Git to manage regression risk during metrics improvement?▼

Yes, Git is required to manage regression risk during metrics improvement. It tracks iterative code adjustments through a series of commits, providing rollback capabilities if an experiment fails verification.

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