learn

Extract lessons from conversations and persist them to AI assistant configuration files.

2|Updated Feb 3, 2026

Search Tags:#refactoring #routing #config #conversations #learn #assistant

Ready to run

npx skills add https://github.com/WhatIfWeDigDeeper/agent-skills --skill learn-whatifwedigdeeper

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/WhatIfWeDigDeeper/agent-skills/tree/main/skills/learn
Command: npx skills add https://github.com/WhatIfWeDigDeeper/agent-skills --skill learn-whatifwedigdeeper

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Analyze the conversation to extract lessons learned, then persist them to AI assistant configuration files.

Core Features & Use Cases

Detect learnings from conversations and surface them for integration into assistant configs.
Persist learnings to Claude Code's CLAUDE.md, Gemini's GEMINI.md, AGENTS.md, Cursor, Copilot, Windsurf, and Continue configurations.
Route learnings by topic, size, and relevance, offering refactoring into skills when content grows.

Quick Start

Analyze your latest conversation and append applicable learnings to the relevant assistant configuration files.

Frequently Asked Questions about learn

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

FAQPage Schema

How do I extract lessons learned from AI conversations and save them to config files?▼

To extract lessons learned from conversations, analyze the chat history and append applicable learnings to assistant configuration files like CLAUDE.md or GEMINI.md. Each learning is validated for relevance and compatibility, then routed by topic and size to the appropriate config.

Can I persist conversation learnings to multiple AI assistant configs like Cursor, Copilot, and Windsurf?▼

Yes, you can persist conversation learnings to multiple AI assistant configs including Claude Code, Gemini, AGENTS.md, Cursor, Copilot, Windsurf, and Continue configurations. Learnings are routed to the relevant configuration files based on the specific topic and context.

What is the best way to organize extracted learnings when configuration content grows large?▼

The best way to organize extracted learnings as content grows is by refactoring them into skills. The system routes learnings by topic, size, and relevance, offering refactoring into skills when necessary to maintain configuration file efficiency and clarity.

How does routing learnings by topic and relevance work for AI assistant configurations?▼

Routing learnings by topic and relevance works by validating each extracted learning for compatibility and relevance, then appending or organizing it into the correct AI assistant configuration file. This ensures learnings are persisted to the most applicable config.

Do I need to manually validate learnings before appending them to AGENTS.md?▼

No, manual validation is not needed before appending learnings to AGENTS.md. The system automatically validates each learning for relevance and compatibility, then appends or organizes it into the configuration based on routing rules.

Why should I persist conversation learnings into AI configuration files instead of keeping them in chat history?▼

Persisting conversation learnings into AI configuration files ensures that extracted lessons are permanently integrated into assistant configs. This allows the AI assistant to continuously apply validated learnings in future interactions, rather than losing them when chat history is cleared.