learning-content-creator

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Transform research materials into structured learning content with bilingual support. Use when users want to create learning content from research, convert research to learning paths, make learning materials, or translate learning content between languages.

practical-stack By practical-stack schedule Updated 2/12/2026

name: learning-content-creator description: Transform research materials into structured learning content with bilingual support. Use when users want to create learning content from research, convert research to learning paths, make learning materials, or translate learning content between languages.

Learning Content Creator

Transform multi-model research materials into structured learning content, with bilingual support (English + Korean).

Quick Start

Workflow Overview

Research Materials → Learning Path (EN) → Translation (KO) → Frontmatter
Phase Input Output
1. Analyze research/*.md files Content outline
2. Create EN Synthesized insights learning/*.en.md
3. Translate KO English content learning/*.ko.md
4. Frontmatter All files YAML metadata added

Workflow Routing

Intent Workflow
Create learning content from research workflows/create-learning.md
Translate EN to KO workflows/translate.md

Note: Phase 4 (Frontmatter) uses the doc-frontmatter schema. The calling command coordinates the multi-skill pipeline.

Phase 1: ANALYZE Research

Goal: Understand and synthesize multi-model research.

Input Structure

docs/NN-topic/
├── research/
│   ├── 00-research-prompt.en.md   # Original prompt
│   ├── 01-claude.en.md            # Claude's response
│   ├── 02-gpt/                    # GPT's response (may be multi-file)
│   │   ├── 01-concepts.en.md
│   │   ├── 02-relationships.en.md
│   │   └── ...
│   └── 03-gemini.en.md            # Gemini's response

Analysis Checklist

Check Question
Coverage What topics do all models agree on?
Unique What unique insights does each model provide?
Conflicts Where do models disagree? How to resolve?
Gaps What's missing? What questions remain?

Output: Content Outline

# Learning Content Outline

## Modules (6-8 recommended)

| # | Module | Topics | Sources |
|---|--------|--------|---------|
| 1 | Fundamentals | Definitions, core concepts | All models |
| 2 | Relationships | How parts connect | GPT, Claude |
| ... | ... | ... | ... |

## Key Insights by Source

- **Claude**: [unique insights]
- **GPT**: [unique insights]
- **Gemini**: [unique insights]

## Synthesis Strategy

[How to combine insights without redundancy]

Phase 2: CREATE English Content

Goal: Create structured learning modules in English.

Directory Structure

docs/NN-topic/
└── learning/
    ├── README.en.md           # Course overview, learning path
    ├── 01-module-name.en.md   # Module 1
    ├── 02-module-name.en.md   # Module 2
    └── ...

Module Template

# Module N: Title

> One-sentence module summary

## Learning Objectives

After completing this module, you will:
- [Objective 1]
- [Objective 2]
- [Objective 3]

---

## N.1 First Section

[Content]

## N.2 Second Section

[Content]

---

## Key Takeaways

- [Takeaway 1]
- [Takeaway 2]
- [Takeaway 3]

## Exercises

### Exercise N.1: [Name]

[Exercise description]

---

## Next Steps

Continue to [Module N+1: Title](./0N+1-title.en.md)

README Template

# Course Title

> Course tagline (one sentence)

## Course Overview

[2-3 paragraph description]

## Who This Is For

- [Audience 1]
- [Audience 2]

## Prerequisites

- [Prerequisite 1]
- [Prerequisite 2]

---

## Course Modules

| # | Module | Duration | Description |
|---|--------|----------|-------------|
| 1 | [Title](./01-name.en.md) | NN min | Description |
| 2 | [Title](./02-name.en.md) | NN min | Description |

**Total Time:** ~N hours

---

## Learning Path

### Beginner Track
[Visual flow diagram]

### Advanced Track
[Visual flow diagram]

---

## Source Materials

| Source | Description |
|--------|-------------|
| [Research Prompt](../research/00-research-prompt.en.md) | Original prompt |
| [Claude](../research/01-claude.en.md) | Claude's response |
| [GPT](../research/02-gpt/) | GPT's response |
| [Gemini](../research/03-gemini.en.md) | Gemini's response |

Writing Guidelines

Guideline Description
Synthesize Don't copy verbatim; synthesize insights
Attribute Note which model contributed which insight
Practical Focus on actionable knowledge
Consistent Use same terminology throughout
Progressive Build complexity gradually

Phase 3: TRANSLATE to Korean

Goal: Create high-quality Korean translations.

Naming Convention

English Korean
*.en.md *.ko.md
README.en.md README.ko.md
01-fundamentals.en.md 01-fundamentals.ko.md

Translation Guidelines

Aspect Guideline
Technical terms Keep English for universally used terms (e.g., Command, Skill, Agent)
Headers Translate headers
Code blocks Keep code in English, translate comments
Tables Translate content, keep structure
Links Update to point to .ko.md counterparts

Do NOT Translate

  • Code snippets
  • File paths
  • Command examples
  • Technical identifiers (kebab-case names, etc.)

Translation Checklist

  • All .en.md files have .ko.md counterparts
  • Internal links updated to .ko.md versions
  • Technical terms consistently handled
  • Tables and diagrams preserved
  • Exercises and examples localized where appropriate

Phase 4: ADD Frontmatter

Goal: Add YAML frontmatter to all learning documents.

Frontmatter Schema

Use the frontmatter schema from doc-frontmatter skill (see .claude/skills/doc-frontmatter/references/schema.md).

Frontmatter Template for Learning Content

---
title: "Module Title"
description: "50-160 char summary of what this module teaches"
type: tutorial
tags: [AI, Architecture, BestPractice]
order: 1
depends_on: [./prerequisite-module.en.md]
related: [./related-module.en.md]
---

Type Selection for Learning

Content Type type Value
Course overview (README) index
Step-by-step module tutorial
Reference/spec reference
Concept explanation explanation

Execution

For each file:

  1. Extract title from H1
  2. Generate description from first paragraph
  3. Determine type based on content
  4. Select relevant tags (max 5)
  5. Set order from filename prefix
  6. Add depends_on/related if applicable

Quality Checklist

Phase 1: Analyze

  • All research files read
  • Key insights extracted from each model
  • Conflicts identified and resolved
  • Content outline created

Phase 2: Create EN

  • All modules follow template
  • Learning objectives are measurable
  • Content synthesizes (not copies) sources
  • Exercises included in each module
  • Links work correctly

Phase 3: Translate KO

  • All files translated
  • Technical terms consistent
  • Links updated to .ko.md
  • Natural Korean (not machine-translation quality)

Phase 4: Frontmatter

  • All files have frontmatter
  • Required fields present (title, description, type)
  • Tags from controlled vocabulary
  • Dependencies correctly specified

Example Output

See docs/01-structure-organizer/learning/ for a complete example:

docs/01-structure-organizer/learning/
├── README.en.md              # Course index (EN)
├── README.ko.md              # Course index (KO)
├── 01-fundamentals.en.md     # Module 1 (EN)
├── 01-fundamentals.ko.md     # Module 1 (KO)
├── 02-relationships.en.md    # Module 2 (EN)
├── 02-relationships.ko.md    # Module 2 (KO)
├── 03-decision-framework.en.md
├── 03-decision-framework.ko.md
├── 04-templates.en.md
├── 04-templates.ko.md
├── 05-examples.en.md
├── 05-examples.ko.md
├── 06-anti-patterns.en.md
└── 06-anti-patterns.ko.md
Install via CLI
npx skills add https://github.com/practical-stack/ai-lab --skill learning-content-creator
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