teaching-pipeline
Full teaching-lifecycle orchestrator for university professors.
Skill by YujxZJCN
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: design, data, agent-building
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/teaching-pipeline
What's inside
- Skill name
teaching-pipeline- Description
- Full teaching-lifecycle orchestrator for university professors. 4-agent team driving the six sibling skills through staged gates over the Course Passport: design → alignment gate → build → assess → quality gate → semester delivery loop → reflection → next-term improvement. Resumable from the passport at any week of the term; mid-entry at any stage. Triggers on: teach a course, prepare my course, semester, full course pipeline, course lifecycle, new semester, what's next for my course, course status, 开课, 备一门课, 新学期, 整门课, 课程全流程, 教学流程, 下一步.
- License
- MIT
- Metadata
- status: active · version: 1.0.0 · last_updated: 2026-06-10 · pipeline_stage: orchestrator
- Instructions
- 212 lines in SKILL.md · view on GitHub
Files (6)
- SKILL.md
- gate_runner_agent.md · agents/
- iteration_coach_agent.md · agents/
- passport_keeper_agent.md · agents/
- pipeline_orchestrator_agent.md · agents/
- pipeline_state_machine.md · references/
SKILL.md (first lines)
# Teaching Pipeline — Course Lifecycle Orchestrator
Orchestrates the whole teaching lifecycle — design, build, assess, deliver, reflect,
improve — by dispatching the six sibling skills in backward-design order over a single
Course Passport (`shared/course_passport_schema.md`). The professor brings the
discipline, the students, and every decision; this skill brings sequence, gates, and
memory across the semester and across terms.
> **Prime rule:** unlike a paper pipeline, teaching is *cyclic and calendar-bound*.
> Stage 4 is a loop, not a step, and Stage 6 feeds Stage 1 of the next term. The
> passport plus today's position in the academic calendar — never the chat history —
> determines what happens next.
## Quick Start
```
I'm teaching a new course on machine learning next semester — run the whole pipeline
新学期要开一门《数据结构》,帮我把整门课准备出来
I already have a syllabus from last year — pick it up from there
It's week 6, what's next for my course?
课程现在什么状态?下一步做什么?
Term just ended, here are my student evals — close out the semester
```
## Modes
| Mode | Trigger intent | What it does |
|------|---------------|--------------|
| `full` | "Teach/prepare a whole course", new course from scratch | Stage 0 onward: intake → passport → all stages in order, every gate, every checkpoint |
| `mid-entry` | Professor arrives with existing materials or mid-process ("I already have a syllabus", "it's week 9") | Detect/ask where they are, validate existing materials into the passport (via course-designer `align-check`, not re-derivation), enter at the matching stage per the routing table below |
| `status` | "What's next?", "course status", 下一步 | Read passport + calendar position; report current stage, gate states, pending confirmations, and the next concrete action. Read-only |
| `new-term` | "Teaching it again", new semester of an existing course | Stage 6 → Stage 1 re-entry: load `iteration_history` evidence + the redesign brief, dispatch course-designer `redesign` with the evidence attached |
| `dashboard` | "Show me my course", "course overview", 课程总览 | Run `python3 scripts/build_dashboard.py <passport>` → single-file `course_dashboard.html` next to the passport: gates (stored + live re-check), outcomes, assessment plan, week-by-week resources with clickable local artifact links, ledger, workload, iteration history. Regenerated at any checkpoint on request — it is a build product of the passport, never hand-edited |
**Mode dispatch rule:** a passport already on disk + a vague request → run `status`
first and propose the next action; never restart `full` on top of an existing passport.
Detect intent in any language.
## Stage Map
```
Stage 0 CONTEXT — intake → initialize Course Passport 🧑 checkpoint
Stage 1 DESIGN — course-designer (full | redesign) 🧑 checkpoint
Gate 1.5 ALIGNMENT — alignment_gate_protocol; BLOCK → back to 1 ✓ machine + professor ack
Stage 2 BUILD — lesson-builder week-batch, in batches the
professor sizes (just-in-time by default) 🧑 checkpoint per batch
Stage 3 ASSESS — assessment-architect per assessment_plan
entry + integrity-check 🧑 checkpoint per instrument
Gate 3.5 QUALITY — quality_gate_protocol; BLOCK → back to 2/3 ✓ machine + professor ack
Stage 4 DELIVER — weekly loop for the whole term:
just-in-time builds · student-mentor on demand
· midcourse feedback at week 4–6 🧑 checkpoint per cycle
Stage 5 REFLECT — teaching-reflector eval-analysis +
evidence triangulation 🧑 checkpoint
Stage 6 IMPROVE — iteration record → passport iteration_history;
prioritized change list; offer re-entry:
next term → Stage 1 redesign with evidence 🧑 checkpoint
```
| Stage | Skill / mode dispatched | Artifacts | Checkpoint / gate |
|-------|------------------------|-----------|-------------------|
| 0 CONTEXT | (this skill) intake | `course_passport.yaml` initialized | 🧑 context confirmed |
| 1 DESIGN | `course-designer` `full` (or `redesign` in `new-term`) | passport design fields, `syllabus.md`, `design_rationale.md` | 🧑 per course-designer's internal checkpoints |
| 1.5 ALIGNMENT | gate_runner → `shared/alignment_gate_protocol.md` | `gates.alignment_gate` findings + status | ✓ machine checks + professor acknowledgment; BLOCK → Stage 1, max 3 rounds |
| 2 BUILD | `lesson-builder` `week-batch` | `lessons/W*` packages, schedule `artifact_refs` | 🧑 per batch |
| 3 ASSESS | `assessment-architect` (`exam`/`quiz`/`project-brief`/`rubric`… per `assessment_plan` type) + `integrity-check` | instruments + rubrics, `ai_resilience` set per assessment | 🧑 per instrument |
| 3.5 QUALITY | gate_runner → `shared/quality_gate_protocol.md` | `gates.quality_gate` findings + status | ✓ machine checks + professor acknowledgment; BLOCK → Stage 2/3, max 3 rounds |
| 4 DELIVER | weekly: `lesson-builder` `week-batch` (next week); `student-mentor` (on demand); `submission-auditor` `spec`/`audit`/`batch-audit` (on demand, when work comes in); `teaching-reflector` `midcourse` (week 4–6) | week materials, mentoring outputs, submission audit reports, midcourse report | 🧑 per weekly cycle; person-affecting outputs per Checkpoint Protocol hard rule |
| 5 REFLECT | `teaching-reflector` `eval-analysis` + triangulation with peer/artifact evidence | evaluation analysis report | 🧑 analysis confirmed |
| 6 IMPROVE | iteration_coach | `iteration_history` entry, prioritized change list, redesign brief | 🧑 record confirmed; offer `new-term` |
**Build-ahead depth (Stage 2):** the pipeline does **not** default to building all 16
weeks up front. At the Stage 2 entry checkpoint the professor chooses a batch depth —
first week only, first unit, through the first exam, or everything. Just-in-time per
week/unit is the recommended default: lessons built months ahead go stale against the
real classroom. The choice is recorded in the passport and drives the Stage 4 loop.
## Mid-Entry Routing
Mid-entry is first-class, not an exception. The orchestrator validates what exists into
the passport (Iron Rule 3) and enters at the earliest stage whose entry invariants are
unmet (`references/pipeline_state_machine.md`).
| "I have…" | Entry point |
|-----------|-------------|
| Nothing — new course, blank page | Stage 0 `full` (offer course-designer `socratic` if aims are vague) |
| An old syllabus / inherited course outline | Stage 0 intake → back-fill passport from the syllabus (confirmed, not assumed) → course-designer `align-check` to validate → Gate 1.5 → Stage 2 (or back to Stage 1 `redesign` if the gate fails) |
| A full confirmed design but no class materials | Validate passport (or build one from the design) → Gate 1.5 if `not_run` → Stage 2 |
| Materials built but no exams/rubrics | Validate → Stage 3 (Gate 1.5 must show `pass`; if `not_run`, run it first — it is cheap and catches what Stage 3 would inherit) |
| Mid-semester, week N, course already running | Validate passport + ask/confirm calendar position → enter the Stage 4 loop at week N; Gates run retroactively only if the professor wants the audit |
| Term just ended, student evals in hand | Validate → Stage 5 (eval-analysis) → Stage 6 |
## Stage 4 — The Weekly Delivery Loop
Stage 4 is the term itself. Each cycle answers **the Monday question**: *"Week N — what's
due?"*
```
each week N of the term:
1. ORIENT — passport + calendar: what's taught in W(N+lead), what assessments are
due/upcoming, what's already built (artifact_refs)
2. BUILD — just-in-time window: lesson-builder week-batch for the next unbuilt
week(s) within the professor's chosen lead time (default: next week)
3. SUPPORT — student-mentor on demand ONLY: feedback batches, a struggling student
the professor brings up, emails, office-hours prep;
submission-auditor when work comes in: spec confirmed at assignment
release, audit/batch-audit at collection
4. MIDCOURSE— at week 4–6 (once): offer teaching-reflector `midcourse` — early
feedback while there is still time to act on it
5. CHECK — 🧑 weekly checkpoint: what shipped, what's pending, next Monday's picture
```
Rules of the loop:
- **Resumable by calendar.** "What week are we in?" is answered from the passport's
stored term calendar + today's date; a fresh session lands in the right cycle without
recap. If the calendar was never stored, ask once and store it (Iron Rule 5).
- **Struggling-student support is on-demand and NEVER auto-initiated.** The pipeline
does not scan grades, attendance, or any data for struggling students — the professorFrom YujxZJCN/teaching-skills, MIT.
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Signals
- Stars
- 41
- Forks
- 7
- Open issues
- 0
- Last commit (this folder)
- Jun 17, 2026 (4 months ago)
- Last release
- Jun 17, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.0.0
- License
- MIT
- Repository
- github.com/YujxZJCN/teaching-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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cohort-analyst
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teaching-pipeline skill. Agent Mart. https://agentmart.dev/skills/yujxzjcn-teaching-pipeline (last updated 2026-10-24)