course-generate
Generate a complete course — learning objectives, syllabus, slides (LaTeX), scripts, and assessments — using the ADDIE multi-agent pipeline. Use when the user asks to "create a course on X", "generate teaching materials for X", "build an undergraduate/graduate course on X", or similar end-to-end course-authoring requests.
Course Generate (Full ADDIE Pipeline)
Runs the complete multi-agent course generation pipeline:
- Phase 1 — Foundation deliberations (learning objectives, resource assessment, target audience, syllabus, assessment planning, final project)
- Phase 2 — Per-chapter development (slides, scripts, assessments via SlidesDeliberation)
- Phase 3 — Evaluation (Program Chair + Test Student review)
This is a long-running task — typically 20–60 minutes depending on model and number of chapters. Confirm scope with the user before launching.
When to invoke this skill
- User asks to generate a course / teaching materials / curriculum
- User provides a topic/subject and wants end-to-end output
- User wants to reproduce the paper's pipeline on new content
Do not invoke for:
- Just converting existing LaTeX → PPTX → use
latex-to-pptx - Only evaluating existing slides → use
slide-evaluate - Optimizing an existing slide chapter → (future:
slide-optimizeskill)
Prerequisites
pip install instructional-agentsOPENAI_API_KEYset in the environment- Disk space ~10–50 MB per course
Usage
python3 "${CLAUDE_PLUGIN_ROOT}/skills/course-generate/scripts/generate.py" \
--course "<course name>" \
[--model <model_name>] \
[--exp-name <tag>] \
[--catalog <catalog_name>] \
[--copilot <copilot_name>]
Arguments
| Arg | Required | Description |
|---|---|---|
--course | yes | Course name/topic, e.g. "Reinforcement Learning" |
--model | no | LLM model (default: gpt-4o-mini) |
--exp-name | no | Subdirectory under exp/ (default: test) |
--catalog | no | Pre-loaded reference catalog name |
--copilot | no | Copilot mode with interactive feedback |
Example
python3 "${CLAUDE_PLUGIN_ROOT}/skills/course-generate/scripts/generate.py" \
--course "Introduction to Reinforcement Learning" \
--model gpt-4o \
--exp-name rl_undergrad_2026
Output structure
exp/<exp-name>/
├── learning_objectives.md
├── resource_assessment.md
├── target_audience.md
├── syllabus.md
├── assessment_planning.md
├── final_project.md
├── chapter_1/
│ ├── slides.tex
│ ├── slides.pdf (if compiled)
│ ├── script.md
│ └── assessment.md
├── chapter_2/...
└── evaluation/
├── program_chair_review.md
└── test_student_review.md
Follow-up skills
After generation you typically want to run:
latex-compile→ produce PDFslatex-to-pptx→ produce editable PowerPoint (per chapter)slide-evaluate→ re-evaluate with different rubrics
Citation
This is the full pipeline from Instructional Agents (arXiv:2508.19611). Please cite if used in published work.