learn

Extract reusable problem-solving patterns from AI sessions into Markdown files.

14|2|Updated Jan 28, 2026
One-click install
npx skills add https://github.com/excatt/superclaude-plusplus --skill learn-excatt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/excatt/superclaude-plusplus/tree/main/skills/learn
Command: npx skills add https://github.com/excatt/superclaude-plusplus --skill learn-excatt

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of identifying, extracting, and saving reusable patterns from your problem-solving sessions, turning unique solutions into a knowledge base for future use.

Core Features & Use Cases

  • Pattern Extraction: Analyzes session transcripts to identify recurring solutions, debugging techniques, and project conventions.
  • Skill Generation: Creates structured Markdown files for each extracted pattern, suitable for a personal knowledge base.
  • Use Case: After successfully resolving a complex authentication issue with a specific workaround, you can use /learn to save this solution as a reusable skill, ensuring you don't have to rediscover it later.

Quick Start

Run the /learn command to analyze the current session for extractable patterns.

Frequently Asked Questions about learn

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

FAQPage Schema
How do I save reusable problem-solving patterns from AI sessions?

To save reusable problem-solving patterns from AI sessions, you can use an extraction tool to analyze session messages and tool calls, identifying high-value debugging techniques to store in structured Markdown files.

What is the best way to extract project conventions from chat transcripts?

Extracting project conventions from chat transcripts involves analyzing session messages and error resolutions to identify recurring solutions, which are then saved as structured Markdown files for continuous learning and future reuse.

Can I automatically generate Markdown knowledge base files from debugging sessions?

Yes, you can automatically generate Markdown knowledge base files from debugging sessions by analyzing the transcript to identify workarounds and techniques, then saving them as structured pattern files for future reference.

Does extracting debugging techniques require any external dependencies?

No, extracting debugging techniques requires no external dependencies, relying solely on internal scripts and references to analyze session messages and generate structured Markdown files for your knowledge base.

Why should I save error resolutions as structured patterns?

You should save error resolutions as structured patterns to build a persistent knowledge base, ensuring that unique debugging workarounds and project-specific conventions are continuously available for future AI-assisted development workflows.