Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add YujxZJCN/teaching-skills --skill teaching-pipelinegit clone --depth 1 https://github.com/YujxZJCN/teaching-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yujxzjcn/teaching-skills/teaching-pipeline)<a href="https://agentmods.dev/skills/yujxzjcn/teaching-skills/teaching-pipeline"><img src="https://agentmods.dev/badge/skills/yujxzjcn/teaching-skills/teaching-pipeline/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yujxzjcn/teaching-skills/teaching-pipeline"><img src="https://agentmods.dev/badge/skills/yujxzjcn/teaching-skills/teaching-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00136 | $0.03773 |
| Opus 5.5 | $0.00054 | $0.01509 |
| Sonnet 5.5 | $0.00027 | $0.00755 |
| Haiku 4.5 | $0.00014 | $0.00377 |
Grade A, and why
teaching-pipeline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 21d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 |
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 21d ago First seen · 228 lines · 136 tokens per session scan A 8196c97c77b1
teaching-pipeline is a skill published in the GitHub repository YujxZJCN/teaching-skills (41 stars, last pushed 22d ago), licensed MIT. It adds 136 tokens to every session and 3,773 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-04.
Other skills, from other repositories
education-expert
Expert-level education technology, learning management systems, and ed-tech platforms. Use when the user mentions edtech, lms, e learning, or assessment, or when the task involves Educational Technology or Standards.
edtech-expert
Expert in education technology, adaptive learning, student analytics, virtual classrooms, assessment tools, and learning management systems. Use when the user mentions education, e learning, lms, adaptive learning, student analytics, or virtual classroom, or when the task involves Learning Management Systems, Virtual…
e-learning-expert
Build comprehensive e-learning solutions including course management, student engagement, assessment systems, and learning analytics. Use when the user mentions an LMS, online courses, SCORM or xAPI, student engagement, assessments and grading, or learning analytics.
criterion-referenced-rubric-generator
Generate a criterion-referenced rubric with descriptive performance levels for a task or objective. Use for marking guides and general curriculum contexts. For Manning programmes where Competent = success, use coherent-rubric-logic-builder instead.
feedback-quality-analyser
Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.
retrieval-practice-generator
Generate retrieval practice questions at varied difficulty levels for a topic or concept. Use when creating quiz starters, revision activities, or low-stakes testing materials.