course-workflow — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited course-workflow (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
Resolve file paths based on your execution 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/.knowledge/ relative to the project root.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.
Once a course is selected, read the course's 00-course.md to get:
status field (in frontmatter)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 contentsKey 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.
| 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.
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:
/gather-screenshots if course has Product Demo SLTs needing context/gather-code-examples if course has Developer Documentation SLTs needing contextassets/screenshots/ or assets/code-examples/context-gatheredDirectory 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
...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.]If the next step involves a skill:
If the next step is manual:
After each phase completes, update 00-course.md:
status field to new valuelast_updated timestampAfter each phase transition, ask:
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]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 skillsWhen starting a workflow session, check workflow-learnings.md for relevant insights:
Surface these as "tips from previous runs."
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.
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]~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.