Individual skill
lab-forge
Executable teaching-artifact builder for STEM professors — pipeline Stage 2 extension. 5-agent team that builds lab and programming assignments as working packages: per-student synthetic datasets with planted, recoverable ground truth, starter-code scaffolds that run as shipped, autograders with visible/hidden test splits, and reference solutions produced by solving and verified by executing. Triggers on: lab assignment, programming assignment, problem set code, dataset for students, synthetic data, starter code, autograder, solution notebook, Jupyter, 实验作业, 编程作业, 数据集, 实验数据, 起始代码, 自动评分, 自动批改, 参考答案.
lab-forge/SKILL.md
Source commit fd0c486e61cb1f065b88133b599e8806dfaeac12
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- Observed behavior
- Instructions only
- Last checked
- Nov 11, 2026
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Repository context
- Repository stars (not skill ratings)
- 49
- Repository last updated
- Oct 3, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-agents Repository topic
- assessment Repository topic
- claude Repository topic
- claude-code Repository topic
- course-design Repository topic
- edtech Repository topic
- higher-education Repository topic
- pedagogy Repository topic
- syllabus Repository topic
- teaching Repository topic
- engineering Derived category
- data Derived category
- testing Derived category
- education Derived category
Files and excerpt
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Browse files
SKILL.mdcore · 10,617 bytesagents/autograder_agent.mddoc · 4,698 bytesagents/dataset_smith_agent.mddoc · 4,491 bytesagents/lab_designer_agent.mddoc · 4,211 bytesagents/solution_verifier_agent.mddoc · 4,705 bytesagents/starter_code_agent.mddoc · 4,191 bytesreferences/autograder_patterns.mddoc · 7,394 bytesreferences/synthetic_data_patterns.mddoc · 7,262 bytestemplates/lab_handout_template.mddoc · 4,305 bytes
Read excerpt
# 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