course-workflow
Skill6 starsChanged 8 months agoMITView on GitHub
Orchestrate course development workflow, track progress, and capture learnings.
In this repository16 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- andamio-cliSkill
- apprenticeSkill
- assess-sltsSkill
- beginnerSkill
- classify-lesson-typesSkill
- compileSkill
- compoundSkill
- draft-sltsSkill
- gather-code-examplesSkill
- gather-screenshotsSkill
- releaseSkill
- self-assess-readinessSkill
- startSkill
- teacherSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
18 rules. About 0 are common, 11 are distinctive, and 7 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈11
Distinctive · estimate
This author's own choices. Worth a look.
7
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 42
If the user says "new", guide them through creating a new course directory with 01-slts.md.
- Distinctive: line 50
Check which workflow artifacts exist:
- Very specific: line 95
Run /gather-screenshots if course has Product Demo SLTs needing context
- Very specific: line 96
Run /gather-code-examples if course has Developer Documentation SLTs needing context
- Distinctive: line 99
Check off items in README as completed
- Very specific: line 100
When all context gathered, update status to context-gathered
- Distinctive: line 140
If the next step involves a skill:
- Distinctive: line 142
If yes, invoke the skill
- Distinctive: line 143
After skill completes, prompt to update status
- Distinctive: line 145
If the next step is manual:
- Very specific: line 152
After each phase completes, update 00-course.md:
- Distinctive: line 155
Add brief note about what was done
- Distinctive: line 159
After each phase transition, ask:
- Very specific: line 179
Phase 9 (mandatory): When lessons are complete, run /compound --rollup to extract all knowledge from the course before promotion.
- Very specific: line 197
When starting a workflow session, check workflow-learnings.md for relevant insights:
- Distinctive: line 216
If no frontmatter exists, add it.
- Distinctive: line 252
Learnings are optional but valuable: Don't force them, but always ask.
- Distinctive: line 255
One course at a time: Don't try to orchestrate multiple courses in parallel.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Skill: Course Workflow Orchestrator
Description
Guides course development through a 11-phase workflow. Reads current status, suggests next steps, invokes appropriate skills, updates status, and captures learnings that improve the process over time.
Instructions
Path Resolution
Resolve file paths based on your execution context:
- Plugin context (
${CLAUDE_PLUGIN_ROOT}is set): Read knowledge from${CLAUDE_PLUGIN_DATA}/knowledge/(user data), falling back to${CLAUDE_PLUGIN_ROOT}/knowledge/(seed data). Write knowledge to${CLAUDE_PLUGIN_DATA}/knowledge/. - Clone/symlink context (default): Read and write knowledge at
knowledge/relative to the project root.
1. List Courses and Select
First, scan courses-in-progress/ for course directories. For each, read 00-course.md to get title and status.
Present a course selection:
## Courses In Progress
| # | Course | Status | Phase |
|---|--------|--------|-------|
| 1 | Andamio for Contributors | revised | 3/11 |
| 2 | Andamio for Course Creators | slts-drafted | 1/11 |
| 3 | Andamio for API Developers | slts-drafted | 1/11 |
Which course are you working on? (Or: "new" to start a new course)If the user says "new", guide them through creating a new course directory with 01-slts.md. The 00-course.md (complete course outline) is built up through the workflow.
2. Determine Current State
Once a course is selected, read the course's 00-course.md to get:
- Current
statusfield (in frontmatter) - Course metadata (title, audience, etc.)
Check which workflow artifacts exist:
00-course.md(complete course outline — the final output)01-slts.md(working file for SLT drafting/revision)02-slts-quality-review.md03-lesson-type-classification.md04-readiness-assessment.md05-delegation-map.mdassets/screenshots/README.md(screenshot checklist)assets/code-examples/README.md(code example checklist)lessons/directory contents
Key insight: 00-course.md is the deliverable — it contains metadata, modules, SLTs, lesson types, and assignments. 01-slts.md is the working file where SLTs are drafted and refined before being incorporated into the course outline.
3. Map Status to Next Action
| Current Status | Phase | Next Action | Skill to Invoke |
slts-drafted | 1→2 | Assess SLT quality, apply fixes to 01-slts.md | /assess-slts |
quality-reviewed | 2→3 | Classify lesson types | /classify-lesson-types |
types-classified | 3→4 | Assess agent readiness | /self-assess-readiness |
readiness-assessed | 4→5 | Create delegation map | (manual) |
delegation-mapped | 5→6 | Gather context assets | /gather-screenshots, /gather-code-examples |
context-gathered | 6→7 | Build lessons | (lesson skills) |
building | 7 | Continue building lessons | (lesson skills) |
lessons-complete | 7→8 | Compile modules for import | /compile |
compiled | 8→9 | Run full course retrospective | /compound --rollup |
compounded | 9→10 | Move to courses/, update COURSES.md | (manual) |
Note: Phase 2 (quality review) now includes applying fixes. No separate "revise" phase — edits happen in place, patterns compound to knowledge base.
3b. Phase 6: Gather Context (Detail)
Phase 6 prepares assets needed before building lessons. The readiness assessment identifies what's missing; the gather skills create checklists for collection.
Invoke based on lesson types:
| Lesson Type | Skill | Output |
| Product Demo | /gather-screenshots | assets/screenshots/README.md |
| Developer Documentation | /gather-code-examples | assets/code-examples/README.md |
| How To Guide | (manual) | Supplementary docs in assets/ |
| Exploration | (usually none) | Framing questions in lesson inputs |
| Organization Onboarding | (manual) | Org-specific context in assets/ |
Workflow:
- Run
/gather-screenshotsif course has Product Demo SLTs needing context - Run
/gather-code-examplesif course has Developer Documentation SLTs needing context - Human captures screenshots / writes code examples following checklists
- Files saved to
assets/screenshots/orassets/code-examples/ - Check off items in README as completed
- When all context gathered, update status to
context-gathered
Directory structure after Phase 6:
courses-in-progress/[course-slug]/
assets/
screenshots/
README.md # Capture checklist
1.2-wallet-connect-01.png
...
code-examples/
README.md # Code checklist
1.2-api-auth.ts
...4. Present Status and Recommendation
Output a status card:
## Course: [Course Title]
**Current Status:** [status] (Phase [n] of 11)
**Progress:** [visual indicator, e.g., ████░░░░░░ 4/11]
### Completed Artifacts
- [x] 01-slts.md
- [x] 02-slts-quality-review.md
- [ ] 03-lesson-type-classification.md
- ...
### Recommended Next Step
[Description of what to do next]
**Action:** [Specific action - invoke skill, manual step, etc.]5. Execute or Guide
If the next step involves a skill:
- Confirm with user: "Ready to run /[skill-name]?"
- If yes, invoke the skill
- After skill completes, prompt to update status
If the next step is manual:
- Explain what needs to be done
- Offer to help with specific sub-tasks
- Prompt to update status when complete
6. Update Status
After each phase completes, update 00-course.md:
- Change
statusfield to new value - Add
last_updatedtimestamp - Add brief note about what was done
7. Capture Learnings
After each phase transition, ask:
- "Any friction in this phase?"
- "Anything that should work differently next time?"
Append learnings to workflow-learnings.md in the project root (create if doesn't exist):
## [Date] - [Course Name] - Phase [n] → [n+1]
**What happened:** [brief summary]
**Friction:** [what was hard or unclear]
**Improvement idea:** [how to make it better]
**Heuristic:** [if a generalizable pattern emerged]7b. Compounding Knowledge
Phase 9 (mandatory): When lessons are complete, run /compound --rollup to extract all knowledge from the course before promotion. This is a required step in the workflow.
Mid-workflow (optional): You can also run compound after specific phases to capture knowledge incrementally:
| Phase Completed | Optional Command |
| quality-reviewed (2→3) | /compound quality-review |
| types-classified (4→5) | /compound classification |
| readiness-assessed (5→6) | /compound readiness |
The /compound skill extracts structured knowledge from artifacts into the knowledge/ directory, which improves future skill runs.
Relationship between files:
workflow-learnings.md= human-readable narrative, captured conversationallyknowledge/*.yaml= machine-readable patterns, consumed by skills
8. Show Accumulated Learnings
When starting a workflow session, check workflow-learnings.md for relevant insights:
- Learnings from the same phase
- Learnings from the same course type
- Recently added heuristics
Surface these as "tips from previous runs."
Status Field Format
The status field in 00-course.md should be in YAML frontmatter:
---
course: Andamio for Contributors
status: quality-reviewed
last_updated: 2026-02-27
---If no frontmatter exists, add it.
Workflow Learnings File
The workflow-learnings.md file accumulates insights across all courses. Structure:
# Workflow Learnings
Insights captured during course development that improve the process over time.
## Phase-Specific Learnings
### Phase 2: Assess SLT Quality
- [learning]
### Phase 4: Classify Lesson Types
- [learning]
...
## Cross-Cutting Heuristics
Patterns that apply across phases:
- [heuristic]
## Course-Specific Notes
### andamio-for-contributors
- [note]Guidelines
- Don't skip phases. The workflow is sequential for a reason. If artifacts are missing, flag it.
- Update status promptly. Status should reflect reality. Stale status causes confusion.
- Learnings are optional but valuable. Don't force them, but always ask.
- Surface relevant history. Previous learnings make each run smarter.
- Manual steps are real steps. Guide them as carefully as automated ones.
- One course at a time. Don't try to orchestrate multiple courses in parallel.
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Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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