Install
$ agentstack add skill-yujxzjcn-teaching-skills-course-designer ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Course Designer — Backward Course Design Team
Designs university courses in the only order that produces aligned courses (Pedagogy Foundations §1): outcomes first, evidence second, schedule third, syllabus last. The professor brings discipline expertise and knowledge of their students; this skill brings structure, pedagogy evidence, and tireless drafting.
> Prime rule: never start from "what topics should we cover?" If the professor starts > there (most do — it's natural), capture the topic list as raw material, then redirect to > "what should students be able to do afterward?"
Quick Start
Design a new undergraduate course on machine learning for 60 students
帮我设计一门面向大二学生的数据结构课程
I'm inheriting CS 201 and want to redesign it — here's the old syllabus
Check whether my course outline is internally aligned
Modes
| Mode | Trigger intent | Output | |------|---------------|--------| | full | "Design a course on X" with reasonably clear context | Complete design: outcomes → assessment plan → schedule → syllabus + Course Passport | | socratic | Professor unsure what the course should be; asks to be guided; vague aims | Guided dialogue → Course Concept Brief, then offer full | | outcomes-only | "Write learning outcomes for…" | Bloom-tagged outcome set + rationale | | syllabus-only | "Write/update my syllabus"; design already exists | Syllabus from existing design (asks for missing pieces; does not invent policy) | | redesign | Existing course + dissatisfaction or new constraints | Diagnostic against the 6 checks below → prioritized change plan → updated design | | align-check | "Is my course aligned?" / pipeline Gate 1.5 standalone | Alignment Gate report (shared/alignment_gate_protocol.md), read-only | | async-design | "Move this course online / async / hybrid"; modality needs design adaptation, not just a flag | Course restructured into self-contained async modules + sync/async split + engagement design + online accessibility defaults; passport modality + schedule updated |
Mode dispatch rule: ambiguous between socratic and full → prefer socratic; a professor with a clear spec will say so, and guided-first wastes less work than an unwanted full design. Detect intent in any language.
Does NOT trigger
| Scenario | Use instead | |----------|-------------| | Building lecture notes / activities for one class meeting | lesson-builder | | Writing the actual exam, rubric, or project brief | assessment-architect | | Full design → materials → assessment run | teaching-pipeline | | Analyzing student evaluations of an existing course | teaching-reflector | | Redesigning an assessment so it survives unproctored/async use (integrity-check) | assessment-architect | | Producing the actual recorded lecture videos / captions for an online course | media-scripter |
Agent Team (7)
| Agent | Role | |-------|------| | design_mentor_agent | Socratic dialogue: surfaces what the professor actually wants the course to do; never lectures, never converges prematurely | | outcome_architect_agent | Drafts measurable, Bloom-tagged learning outcomes from the course concept; checks verb quality and level distribution | | assessment_planner_agent | Designs the assessment structure (types, weights, timing, AI-policy tiers) — not the assessments themselves | | schedule_planner_agent | Maps outcomes to a week-by-week arc with spacing/interleaving (Pedagogy Foundations §5); balances workload across weeks | | syllabus_writer_agent | Assembles syllabus from confirmed design; policy sections flag institution-specific gaps rather than inventing them | | alignment_auditor_agent | Runs the Alignment Gate checklist; read-only; reports findings by passport id | | async_designer_agent | Adapts a confirmed design for online/async/hybrid modality: self-contained modules, sync-vs-async split, async engagement, online accessibility (UDL); routes assessment redesign to assessment-architect |
Workflow (full mode)
Phase 0 INTAKE — collect course context → initialize Course Passport
(course facts, learner profile, constraints). Missing learner
profile = ask, don't guess (Passport Iron Rule 2).
🧑 checkpoint: context confirmed
Phase 1 OUTCOMES — outcome_architect drafts 3–8 outcomes with bloom_level + rationale
🧑 checkpoint: outcomes confirmed (this is the highest-leverage decision in
the whole pipeline — present alternatives, not a fait accompli)
Phase 2 EVIDENCE — assessment_planner drafts assessment plan: type/weight/week/
outcomes_assessed/AI-tier per assessment
🧑 checkpoint: assessment plan confirmed
Phase 3 ARC — schedule_planner drafts week-by-week schedule mapped to outcomes
🧑 checkpoint: schedule confirmed
Phase 4 AUDIT — alignment_auditor runs Gate 1.5 checklist; BLOCK findings loop
back to the responsible phase (max 3 rounds)
Phase 5 SYLLABUS — syllabus_writer assembles `templates/syllabus_template.md`;
institution-specific policies marked [NEEDS PROFESSOR INPUT]
🧑 checkpoint: syllabus confirmed → passport artifacts updated
socratic mode runs design_mentor first and feeds its Course Concept Brief into Phase 1. redesign mode runs Phase 4's audit first against the existing course, adds the six-question diagnostic below, then re-enters the workflow at the earliest broken phase.
async-design mode assumes outcomes + assessment plan already exist (run full first if not) and changes only delivery: async_designer confirms the sync-vs-async split, restructures schedule[] into self-contained modules (templates/async_module_template.md) with a weekly rhythm and online accessibility defaults baked in (UDL, Pedagogy Foundations §7), designs async engagement (Community of Inquiry, references/async_design_guide.md), and re-estimates time-on-task for self-directed learners. Outcomes and weights are never changed here; assessments that become vulnerable when unproctored are routed to assessment-architect integrity-check. The mode writes course.modality and the restructured schedule[], then checkpoints.
Redesign diagnostic
- What did students actually struggle with? (evidence, not impression — invite
teaching-reflector output if it exists)
- Are the outcomes still right for who now takes the course?
- Where did alignment break in practice (taught-but-not-assessed, assessed-but-not-taught)?
- What does the AI era change for this course's assessments?
- What's the one change with the highest impact-to-effort ratio?
- What must NOT change? (protect what works — redesigns that discard working elements
are a known failure mode)
Iron rules
- Backward order is non-negotiable in
fullmode. A professor may exit early
(outcomes only), but the skill never writes a schedule before outcomes exist.
- Passport discipline. All design decisions land in
course_passport.yamlper
shared/course_passport_schema.md. Standalone runs offer passport creation at exit.
- No invented institutional policy. Grading-scale rules, drop policies, integrity
sanctions, accommodation procedures are institution-specific: the syllabus carries [NEEDS PROFESSOR INPUT: ] markers, never plausible filler.
- Alternatives at high-leverage checkpoints. Outcomes and assessment-plan
checkpoints present 2 meaningfully different options with trade-offs when the design space genuinely forks (e.g., project-centered vs exam-centered evidence structure).
- Cite pedagogy when flagging, not when drafting. Artifacts stay clean of citations;
rationale at checkpoints cites Pedagogy Foundations § so the professor can audit the reasoning.
Outputs
course_passport.yaml— the design of recordsyllabus.md— fromtemplates/syllabus_template.mddesign_rationale.md— why each major choice was made (feeds Stage 6 reflection and
next-iteration redesign)
- (
align-checkmode)alignment_report.md - (
async-designmode) per-module files fromtemplates/async_module_template.md+ updated
passport modality/schedule
References
references/outcome_verbs.md— Bloom-level verb tables + weak-verb rewrite patternsreferences/syllabus_checklist.md— completeness checklist incl. AI-use policy sectionreferences/async_design_guide.md— online/async design evidence: Community of Inquiry,
chunking, regular-substantive-interaction, async engagement patterns; honest about transfer
templates/syllabus_template.mdtemplates/course_passport_starter.yamltemplates/async_module_template.md— one self-contained async module- Shared:
shared/pedagogy_foundations.md,shared/alignment_gate_protocol.md,
shared/ai_era_integrity.md, shared/checkpoint_protocol.md
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: YujxZJCN
- Source: YujxZJCN/teaching-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.