document-learnings

document-learnings Skill

Purpose: A lightweight, frictionless way to automatically document solved problems, bug fixes, and new learnings into searchable markdown files.

Overview

This skill captures learnings immediately after confirming a solution, creating simple, structured documentation that serves as a searchable knowledge base. All learnings are saved in a flat directory structure with basic YAML frontmatter.

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3-Step Process

Step 1: Gather Context

Auto-invoke after phrases:

• "that worked"
• "it's fixed"
• "problem solved"
• "good to know"

OR manual: /learn command

Extract the following from the conversation history:

1. Topic/Symptom: Brief description of the issue or the concept learned.
2. Solution/Takeaway: What was the fix or the key learning?

If context is completely missing, briefly ask the user: "What was the key learning or fix you'd like to document?"

Step 2: Create File

Generate a simple, sanitized filename: docs/learnings/YYYY-MM-DD-[short-topic].md

Sanitization rules:

• Lowercase
• Replace spaces with hyphens
• Truncate to reasonable length (< 50 chars)

Ensure the directory exists:

mkdir -p docs/learnings

Write the documentation file populated with the context gathered in Step 1. Use the following simple template:

---
date: [YYYY-MM-DD]
topic: [Short Topic]
---

# [Topic/Symptom]

## The Problem / Context
[Clear description of the issue or what was being attempted]

## The Solution / Learning
[Explanation of how it was fixed or the key takeaway]

Step 3: Confirm

Once the file is created, present a simple confirmation to the user:

✓ Learning documented!

Saved to: docs/learnings/[filename].md

Return control to the user. No complex decision menus or cross-referencing required.

</critical_sequence>

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Execution Guidelines

MUST do:

• Create the docs/learnings/ directory before writing (mkdir -p).
• Ensure basic markdown formatting.
• Keep the generated documentation concise and to the point.

MUST NOT do:

• Block the user with strict schema validation.
• Ask for excessive details if the conversation history already contains the solution.