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 lab-forgegit 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/lab-forge)<a href="https://agentmods.dev/skills/yujxzjcn/teaching-skills/lab-forge"><img src="https://agentmods.dev/badge/skills/yujxzjcn/teaching-skills/lab-forge/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/lab-forge"><img src="https://agentmods.dev/badge/skills/yujxzjcn/teaching-skills/lab-forge.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 | $0.00142 | $0.02302 |
| Opus 5.5 | $0.00057 | $0.00921 |
| Sonnet 5.5 | $0.00028 | $0.00460 |
| Haiku 4.5 | $0.00014 | $0.00230 |
Grade A, and why
lab-forge 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lab Forge — Executable Teaching-Artifact Team
Builds the artifacts a STEM assignment is actually made of: the dataset students load,
the scaffold they fill in, the tests that grade them, the solution that proves the whole
thing is doable. Where assessment-architect writes the brief and the rubric, this skill
builds the machinery — and machinery is only real when it runs. Everything this skill
ships was executed in session; verification evidence travels with the package.
Prime rule: executed, not assumed. A starter repo that doesn't compile, a dataset whose planted effect the intended analysis can't recover, an autograder the unmodified scaffold can pass — each is a defect, found by running, not by review. Verification is part of the build, never an optional final step.
Quick Start
Build the Week 6 regression lab for STAT 210 — it's A3 in the passport
给我的机器学习课做一个编程作业：起始代码 + 自动评分
Generate a per-student dataset for the ANOVA lab — 45 students, same difficulty each
Write the autograder for this assignment spec; here's the starter repo
Make 4 variants of last year's pathfinding lab so sections can't share answers
我需要这次实验的参考答案和评分说明
Modes
| Mode | Trigger intent | Output |
|---|---|---|
lab |
"Build the lab / programming assignment for…" | Complete package: handout + starter + data + verified solution + grader + verification record |
dataset |
"Generate data for…" / per-student data requests | Synthetic dataset(s) with planted, recoverable properties; per-student/per-section variants; professor-only ground-truth doc |
starter-code |
"Starter code / scaffold / skeleton for…" | Scaffold repo: structure, stubs with full contracts, fixed vs student zones fenced, runs as shipped |
autograder |
"Autograder / tests to grade this" | Test-suite grader: visible tests for students + hidden tests for grading, partial-credit map, submission-auditor-consumable output |
solution |
"Reference solution / solution notebook for…" | Solution produced by solving from student-facing materials, verified by execution, + grading notes |
variant |
"Make N versions of this lab/dataset" | N difficulty-equivalent variants with the equivalence argument stated and spot-checked |
What ships with it
8 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.
- agents/autograder_agent.md 4.6 KB
- agents/dataset_smith_agent.md 4.4 KB
- agents/lab_designer_agent.md 4.1 KB
- agents/solution_verifier_agent.md 4.6 KB
- agents/starter_code_agent.md 4.1 KB
- references/autograder_patterns.md 7.2 KB
- references/synthetic_data_patterns.md 7.1 KB
- templates/lab_handout_template.md 4.2 KB
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 · 161 lines · 142 tokens per session scan A 968b5e6f94db
lab-forge is a skill published in the GitHub repository YujxZJCN/teaching-skills (41 stars, last pushed 22d ago), licensed MIT. It adds 142 tokens to every session and 2,302 once invoked, about $0.0006 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.
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