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lesson-generator
Generate lesson content following 4-Layer Teaching Framework with standardized metadata and Docusaurus conventions
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Generate lesson content following 4-Layer Teaching Framework with standardized metadata and Docusaurus conventions
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Creates assessments with varied question types (MCQ, code-completion, debugging, projects) aligned to learning objectives with meaningful distractors based on common misconceptions. Activate when educators design quizzes, exams, or tests measuring understanding; need questions at appropriate cognitive levels (Bloom's taxonomy); want balanced cognitive distribution (60%+ non-recall); or require rubrics for open-ended questions. Generates MCQs with diagnostic distractors, code-writing prompts, debugging challenges, and project-based assessments targeting deep understanding.
Integrate OpenAI ChatKit framework with custom backend and AI agents. Handles ChatKit server implementation, React component integration, context injection, and conversation persistence.
This skill should be used when scaffolding complex concepts for learners. It applies cognitive load architecture principles to break down concepts into digestible pieces while respecting learning science limits.
Docusaurus file naming, syntax, and structure conventions for RoboLearn platform
This skill should be used when deploying a Docusaurus site to GitHub Pages. It automates the configuration, building, and deployment process, handling GitHub Pages setup, environment configuration, and CI/CD automation. Includes local validation before GitHub Actions triggering.
Design simulation worlds using SDF with ground planes, models, physics configuration, and lighting
| name | lesson-generator |
| description | Generate lesson content following 4-Layer Teaching Framework with standardized metadata and Docusaurus conventions |
| domain | authoring |
| version | 1.0.0 |
| created | "2025-11-28T00:00:00.000Z" |
| updated | "2025-11-29T00:00:00.000Z" |
| triggers | ["Creating new lessons for any module","Generating lesson drafts from specifications","Ensuring consistent lesson structure across books"] |
| dependencies | ["docusaurus-conventions (file naming, MDX syntax)"] |
| learned_from | ["Module 1 ROS 2 implementation metadata standardization (2025-11-29)"] |
Think like a curriculum designer who creates consistent, high-quality lessons that build progressively. You ensure every lesson has complete metadata, follows the 4-Layer Teaching Framework, and respects hardware tier constraints.
Before generating any lesson content, ask yourself:
Q: What module and chapter is this lesson in?
Q: What lessons come before and after?
Q: What is the target proficiency level?
.md (not .mdx)< in prose.md and README.mddocusaurus-conventions skill---
id: lesson-{chapter}-{lesson}-{slug}
title: "Lesson {C}.{L}: {Title}"
sidebar_position: {N}
sidebar_label: "{C}.{L} {Short Title}"
description: "{One-line description for SEO and previews}"
duration_minutes: {45|60|75|90}
proficiency_level: "{A2|B1|C2}"
layer: "{L1|L2|L3|L4}"
hardware_tier: {1|2|3|4}
learning_objectives:
- "{Objective 1 using Bloom's verb}"
- "{Objective 2}"
- "{Objective 3}"
skills:
- "{skill-slug-1}"
- "{skill-slug-2}"
cognitive_load:
new_concepts: {N}
tier_1_path: "{Cloud fallback description}"
generated_by: "content-implementer v1.0.0"
created: "{YYYY-MM-DD}"
version: "1.0.0"
---
| Field | Required | Description | Example |
|---|---|---|---|
id | Yes | Unique across all docs | lesson-1-1-digital-to-physical |
title | Yes | Full lesson title | "Lesson 1.1: From ChatGPT to Walking Robots" |
sidebar_position | Yes | Order in sidebar | 1 |
sidebar_label | Yes | Short label for sidebar | "1.1 Digital to Physical" |
description | Yes | SEO/preview text | "Understanding differences between software and embodied AI" |
duration_minutes | Yes | Expected completion time | 45 |
proficiency_level | Yes | CEFR-aligned level | "A2", "B1", "C2" |
layer | Yes | Teaching layer | "L1", "L2", "L3", "L4" |
hardware_tier | Yes | Minimum hardware required | 1 (cloud), 2 (GPU), 3 (Jetson), 4 (robot) |
learning_objectives | Yes | Measurable outcomes (3-5) | Array of strings |
skills | Yes | Related skill slugs | ["ros2-fundamentals", "ros2-cli"] |
tier_1_path | Recommended | Cloud fallback | "Cloud ROS 2 (TheConstruct)" |
cognitive_load.new_concepts | Recommended | Concept count | 7 |
generated_by | Yes | Generator attribution | "content-implementer v1.0.0" |
created | Yes | Creation date | "2025-11-29" |
version | Yes | Content version | "1.0.0" |
| Deprecated | Use Instead |
|---|---|
cefr_level | proficiency_level |
duration | duration_minutes |
estimated_time | duration_minutes |
chapter / lesson | id with pattern |
Always generate complete metadata BEFORE content.
The metadata defines:
L1 (Manual Foundation):
L2 (AI Collaboration):
L3 (Intelligence Design):
L4 (Spec-Driven):
Every lesson must specify:
hardware_tier (1-4)tier_1_path fallback for cloud users**Hardware Tier**: {N} | **Cloud Path**: {fallback description}
ID Pattern: lesson-{chapter}-{lesson}-{slug}
lesson-1-1-digital-to-physicallesson-3-4-services-parameterslesson-7-3-testing-validationSidebar Label Pattern: "{C}.{L} {Short Title}"
"1.1 Digital to Physical""3.4 Services & Parameters""7.3 Testing Validation"---
[Complete frontmatter - see above]
---
# {Lesson Title}
**Duration**: {N} minutes | **Layer**: {L1-L4} | **Tier**: {N} ({description})
{Opening hook - 2-3 paragraphs motivating the topic}
## Learning Objectives
By the end of this lesson, you will be able to:
- {Objective 1}
- {Objective 2}
- {Objective 3}
## {Section 1: Core Content}
{Layer-appropriate content}
### {Subsection}
{Progressive explanation}
## {Section 2: Practice/Application}
{Hands-on content appropriate to layer}
## {Section 3: Assessment} (optional for L1)
{Understanding validation}
## Try With AI
{AI collaboration prompts - required for L2+}
---
**Previous:** [Link] | **Next:** [Link]
id is unique and follows patternproficiency_level not cefr_levelduration_minutes not durationskills array populatedhardware_tier specifiedtier_1_path for tier > 1.md< in prose.md extensionThis skill is typically invoked by:
content-implementer agent during /sp.implementDependencies:
docusaurus-conventions - File naming and syntaxlearning-objectives - Bloom's taxonomy alignmentassessment-builder - Proficiency-appropriate assessments| Version | Date | Change |
|---|---|---|
| 0.1.0 | 2025-11-28 | Initial placeholder |
| 1.0.0 | 2025-11-29 | Full implementation with metadata standards from Module 1 |