learn-patterns

Name: learn-patterns
Availability: InStock
Author: GDSDN

Analyzes historical code changes to identify and suggest reusable modification patterns.

3|Updated Feb 7, 2026

Search Tags:#code quality #automation #developer tools #refactoring #code patterns #ai assisted development

Ready to run

npx skills add https://github.com/GDSDN/kord-aios --skill learn-patterns

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: learn-patterns
Source: https://github.com/GDSDN/kord-aios/tree/main/src/features/builtin-skills/kord-aios/analysis/learn-patterns
Command: npx skills add https://github.com/GDSDN/kord-aios --skill learn-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires fs, path, chalk, inquirer, and includes scripts (resource) components.

What problem does it solve?

This Skill automates the process of learning from successful code modifications, identifying reusable patterns, and applying them to future development tasks to improve efficiency and quality.

Core Features & Use Cases

Pattern Learning: Analyzes past code changes to identify recurring successful patterns in areas like refactoring, structural changes, and performance improvements.
Pattern Application: Suggests relevant learned patterns for new modifications, providing guidance on how to apply them.
Use Case: A developer is about to refactor a complex module. This Skill can analyze past successful refactorings of similar modules and suggest proven patterns to ensure the new refactoring is efficient and effective.

Quick Start

Use the learn-patterns skill to learn from the last 100 modifications.

Frequently Asked Questions about learn-patterns

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

FAQPage Schema

How do I identify reusable refactoring patterns from historical code changes?▼

You identify reusable refactoring patterns by analyzing historical code modifications using AST analysis and similarity calculations. This approach detects recurring structural changes and performance improvements to provide intelligent suggestions for future development tasks.

How does AST analysis work for learning code modification patterns?▼

AST analysis works for learning code patterns by parsing code modifications into abstract syntax trees to calculate structural similarity. It identifies recurring changes across refactoring tasks and registers matching components to recommend reusable structural and dependency patterns.

Can I use historical data to suggest refactoring patterns for new development tasks?▼

You can use historical data to suggest refactoring patterns by analyzing past successful code modifications. The system identifies proven patterns from similar modules and provides actionable guidance to apply them efficiently to your new development tasks.

What's the best way to automate learning from successful code modifications?▼

The best way to automate learning from successful code modifications is applying a pattern recognition system that analyzes historical data. It uses AST analysis and a component registry to extract reusable code, structural, and performance patterns for future application.

Does this code pattern analysis approach work with AI assisted development workflows?▼

This code pattern analysis approach works with AI assisted development workflows by providing intelligent suggestions derived from historical data. It integrates into developer tools to recommend proven refactoring and structural patterns during active code modification tasks.

When should I not rely on automated code pattern suggestions for refactoring?▼

You should not rely on automated code pattern suggestions when historical data is insufficient or when a module's complexity requires unique structural changes. Pattern application provides guidance based on past similarities, but novel architecture may need manual refactoring strategies.