Collaboratively produce an online course's curriculum, lesson plans, quizzes, and hands-on labs through an agent team, all in one pass.
Execution Mode
Agent Team — Five agents communicate directly via SendMessage and cross-validate each other's work.
Agent Roster
| Agent | File | Role | Type |
|---|---|---|---|
| curriculum-designer | .claude/agents/curriculum-designer.md |
Learning objectives, curriculum structure | general-purpose |
| content-writer | .claude/agents/content-writer.md |
Lesson plans, slides, instructor notes | general-purpose |
| quiz-maker | .claude/agents/quiz-maker.md |
Formative assessment, summative assessment, feedback | general-purpose |
| lab-designer | .claude/agents/lab-designer.md |
Hands-on labs, projects, rubrics | general-purpose |
| course-reviewer | .claude/agents/course-reviewer.md |
Learning objective alignment, coverage validation | general-purpose |
Workflow
Phase 1: Preparation (Performed Directly by the Orchestrator)
- Extract from user input:
- Course Topic: Subject/field the course covers
- Target Learner: Beginner/Intermediate/Advanced, background knowledge
- Course Scale: Total learning time, number of modules
- Lab Environment (optional): Tools, languages, platforms to use
- Existing Files (optional): Curriculum, lesson plans, etc.
- Create the
_workspace/directory at the project root - Organize input and save to
_workspace/00_input.md - If existing files are available, copy to
_workspace/and skip the corresponding phase - Determine execution mode based on scope
Phase 2: Team Assembly and Execution
| Order | Task | Owner | Dependency | Deliverable |
|---|---|---|---|---|
| 1 | Curriculum design | curriculum-designer | None | _workspace/01_curriculum.md |
| 2a | Lesson plan writing | content-writer | Task 1 | _workspace/02_lesson_plans.md |
| 2b | Quiz creation | quiz-maker | Task 1 | _workspace/03_quizzes.md |
| 2c | Lab design | lab-designer | Task 1 | _workspace/04_labs.md |
| 3 | Course review | course-reviewer | Tasks 2a, 2b, 2c | _workspace/05_review_report.md |
Tasks 2a (lessons), 2b (quizzes), and 2c (labs) run in parallel. All depend only on Task 1 (curriculum).
Inter-agent communication flow:
- curriculum-designer completes -> delivers per-lesson objectives and concepts to content-writer; Bloom's level ratios to quiz-maker; lab environment and scenarios to lab-designer
- content-writer completes -> delivers key concepts and examples to quiz-maker (as item material); lesson content to lab-designer (for lab alignment)
- course-reviewer cross-validates all deliverables. On RED Must Fix findings, sends revision requests -> rework -> re-validate (up to 2 cycles)
Phase 3: Integration and Final Deliverables
- Verify all files in
_workspace/ - Confirm all RED Must Fix items have been addressed
- Report final summary to user
Execution Modes by Scope
| User Request Pattern | Execution Mode | Agents Deployed |
|---|---|---|
| "Create an online course," "full course design" | Full Pipeline | All 5 agents |
| "Just design the curriculum" | Curriculum Mode | curriculum-designer + reviewer |
| "Write lesson plans for this curriculum" (existing file) | Lesson Plan Mode | content-writer + reviewer |
| "Just create quizzes" | Quiz Mode | quiz-maker + reviewer |
| "Just design lab assignments" | Lab Mode | lab-designer + reviewer |
Using Existing Files: If the user provides a curriculum, lesson plans, etc., copy to _workspace/ and skip the corresponding agent.
Data Transfer Protocol
| Strategy | Method | Use Case |
|---|---|---|
| File-based | _workspace/ directory |
Store and share major deliverables |
| Message-based | SendMessage | Real-time key information delivery, revision requests |
| Task-based | TaskCreate/TaskUpdate | Progress tracking, dependency management |
File naming convention: {order_number}_{deliverable}.{extension}
Error Handling
| Error Type | Strategy |
|---|---|
| Insufficient domain expertise | Supplement with web search; note "External verification recommended" in report |
| Lab environment unclear | Default to free cloud tools (Google Colab, etc.) |
| Agent failure | Retry once -> proceed without that deliverable; note in review report |
| RED found in review | Send revision request -> rework -> re-validate (up to 2 cycles) |
| Learning objective gap discovered | Request supplementary content from the relevant agent |
Test Scenarios
Normal Flow
Prompt: "Design a 10-hour online course for Python web development beginners, focused on the Flask framework." Expected Result:
- Curriculum: 3-4 modules, 3-5 lessons each, Bloom's-based learning objectives
- Lesson plans: Per-lesson teaching flow, slide outlines, code examples
- Quizzes: Formative (3-5 items per lesson) + Summative (10 items per module)
- Labs: Per-lesson coding labs + Capstone project (simple web app)
- Review: Learning objective coverage matrix with full mapping
Existing File Flow
Prompt: "Create quizzes and lab assignments from this curriculum" + attached curriculum file Expected Result:
- Copy existing curriculum to
_workspace/01_curriculum.md - Combined quiz + lab mode: deploy quiz-maker + lab-designer + reviewer
- Skip curriculum-designer and content-writer
Error Flow
Prompt: "Just design a quick curriculum on data analysis" Expected Result:
- Switch to curriculum mode (curriculum-designer + reviewer)
- Target learner unclear; default to "beginner (non-specialist)" and note in report
- Review report notes "Lesson plans/quizzes/labs not generated"
Agent Extension Skills
| Agent | Extension Skill | Knowledge Provided |
|---|---|---|
| curriculum-designer, content-writer | /learning-design |
Bloom's Taxonomy, Backward Design, Gagne's 9 Events, Cognitive Load Theory |
| quiz-maker | /assessment-engineering |
Item type design, distractor psychology, rubric construction, feedback formulas |
| lab-designer | /lab-scaffolding |
5-level pyramid, starter code design, capstone structure, hint systems |