Can I add my own notes when saving a point?

Yes, you can provide an optional memo argument with the command to add personal context to your saved learning point.

Where is my learning data stored?

All stashed data is stored locally on your machine in the ~/.learn-quest/stash/ directory as JSON files, ensuring privacy and portability.

Does it require manual triggering every time?

While you can trigger it manually, the skill also features a hook that can prompt you to stash learning points automatically upon task completion.

What exactly does the Stash skill save?

It captures a structured summary of your work, including technical decisions made, specific code patterns used, relevant CS concepts, and optional user memos.

How do I access my saved learning points later?

You can review and study your saved items using the companion command /learn-quest:study.

Learn Quest Stash

Name: Learn Quest Stash
Author: gilverse-icn

bygilverse-icn

•

Aprendizaje y Documentación

Saves key learning points and code patterns from your current coding session for later review and study.

Acerca de

Learn Quest Stash is a specialized utility for developers who want to capture educational insights without breaking their flow. By analyzing current conversations and code changes, the skill automatically extracts architectural decisions, library usage, and complex concepts into a structured local repository. This allows you to focus on immediate task completion while building a personalized backlog of 'quests' to study during dedicated learning time, ensuring that valuable technical discoveries are never lost in your terminal history.

Características Principales

Structured Local Storage: Saves learning points, code snippets, and metadata as JSON for offline access.
Custom Memos: Allows users to attach personal notes to stashed items for added context.
Progress Management: Tracks learned status and timestamps to help manage your technical study queue.
1 GitHub stars
Automatic Summarization: Generates concise titles and summaries from complex coding sessions.
Contextual Analysis: Automatically identifies patterns, decisions, and CS concepts from current work.

Casos de Uso

Document the reasoning behind architectural decisions for future technical debt reviews.
Save complex API patterns or library features discovered during development to study later.
Capture unfamiliar computer science concepts mentioned by the AI for deeper research after hours.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add gilverse-icn/learn-quest stash

For use in Claude.ai and ChatGPT

Download Skill

GitHub

Acerca de

Características Principales

Structured Local Storage: Saves learning points, code snippets, and metadata as JSON for offline access.
Custom Memos: Allows users to attach personal notes to stashed items for added context.
Progress Management: Tracks learned status and timestamps to help manage your technical study queue.
1 GitHub stars
Automatic Summarization: Generates concise titles and summaries from complex coding sessions.
Contextual Analysis: Automatically identifies patterns, decisions, and CS concepts from current work.

Casos de Uso

Document the reasoning behind architectural decisions for future technical debt reviews.
Save complex API patterns or library features discovered during development to study later.
Capture unfamiliar computer science concepts mentioned by the AI for deeper research after hours.