| name | build-course |
| description | Explore a target codebase and generate a complete course for it in the M:\Courses platform. Use when the user wants to create a course about another project, codebase, or tool — e.g. "build a course for M:\ai-dev-net", "create a course about this repo", "make a course on X". |
Build Course
Explore a target codebase, design a curriculum, then write all course files into M:\Courses\courses\.
Before writing a single lesson, read the authoring reference:
M:\Courses\courses\How to Create Courses\ — every lesson in that course is a spec. Follow it exactly for structure, callout syntax, quiz frontmatter, and quality rules.
Inputs
The user provides:
- Target codebase path — the repo to learn from (e.g.
M:\ai-dev-net)
- Audience (optional) — who will take the course; default to "developers"
- Depth (optional) — "intro" (3–4 modules) or "deep" (6–8 modules); default "intro"
Phase 1 — Read the Authoring Guide
Spawn an Explore subagent against M:\Courses\courses\How to Create Courses\ and extract:
- Required file/folder structure and naming conventions
- Lesson writing pattern (4-part structure, Key Takeaway rule)
- Callout syntax and available types
- Quiz frontmatter schema
- Content quality checklist
Hold this as your authoring rulebook for the rest of the skill.
Phase 2 — Explore the Target Codebase
Spawn a second Explore subagent against the target path. Ask it to return:
- What the project is — purpose, problem it solves, primary tech stack
- Key concepts & mental models — domain terms, core abstractions, architecture patterns
- User-facing features — what someone does with it day to day
- Getting-started path — setup steps, entry points, first meaningful thing a learner can do
- Non-obvious gotchas — anything that trips up newcomers
Search across README files, docs/, src/ entry points, config files, and example/demo directories.
Run Phases 1 and 2 in parallel.
Phase 3 — Design the Curriculum
Using both outputs, design the course before writing any files:
-
Course metadata
courseId: slugified title (lowercase, hyphens, no spaces)title, subtitle, audience
-
Module plan (3–4 for intro, 6–8 for deep)
- Each module: a thematic cluster of 4–6 lessons + 1 quiz
- Module overview title pattern:
# Module N Overview: {Theme}
- Progression: orient → understand → apply → assess
-
Lesson plan per module
- Files numbered from
1-module-overview.md through N-{topic}.md
- Final file per module: the quiz (e.g.
7-{theme}-quiz.md)
- File names: lowercase, hyphen-separated, numeric prefix
-
Quiz design (5–8 questions per module)
- Four options each; one correct answer that exactly matches an option string
- Include a brief explanation per question
Output the plan as a brief list and confirm the structure is sound before writing.
Phase 4 — Write the Course Files
Courses root: M:\Courses\courses\
Folder layout
M:\Courses\courses\{Course Folder Name}\
├── course.json
├── 1-intro.md
└── modules\
├── 01\
│ ├── 1-module-overview.md
│ ├── 2-{topic}.md
│ ├── ...
│ └── N-{theme}-quiz.md
├── 02\
└── ...
- Course folder name = title as written (spaces preserved), e.g.
AI Dev Studio Fundamentals
- Module folders: zero-padded two digits (
01, 02, … 10)
course.json
{
"courseId": "{{courseId}}",
"title": "{{title}}",
"subtitle": "{{subtitle}}",
"audience": "{{audience}}"
}
1-intro.md frontmatter
---
courseId: {{courseId}}
title: {{title}}
subtitle: {{subtitle}}
audience: {{audience}}
---
Lesson template (follow the 4-part structure from the authoring guide)
Every content lesson must end with a ## Key Takeaway section — one crisp sentence.
Quiz frontmatter
---
lessonType: quiz
passThreshold: 80
maxAttempts: 2
resetScopeOnFail: module
questions:
- prompt: "{{Question?}}"
options:
- "{{A}}"
- "{{B}}"
- "{{C}}"
- "{{D}}"
answer: "{{A}}"
explanation: "{{Why A is correct}}"
---
Quality Checklist
