Uv Create Paper Exercises

Create exercises from a paper

Goal

From a single paper, generate two exercise tracks:

1. Programming: turn the central technique into a coding problem with a crisp spec + tests.
2. Modeling: turn the paper’s formulas/derivations into calculation problems with worked solutions.

The output should be an exercise pack with:

• Clear prompts
• Golden solutions
• Automated checkers
• Local mini-skills to check answers on demand

Output location

Create the pack under:

• $HUMAN_MATERIAL_PATH/exercises/<paper_slug>/

Downloads/clones should go under (gitignored):

• $HUMAN_MATERIAL_PATH/.references/ (PDFs, arXiv zips, cloned repos)

Scaffold the pack

Use the scaffold script to create the file structure:

# Run from this skill directory (the folder containing this SKILL.md):
python scripts/scaffold_exercise_pack.py --slug <paper_slug>

Then fill in the prompts/solutions based on the paper.

Programming exercise workflow

1. Find the central technique:
   • Identify the smallest “core loop” that makes the method work (data structure + algorithm).
2. Extract a clean problem:
   • Define input/output precisely.
   • Specify constraints.
   • Provide 2–3 small examples.
3. Create a testable interface:
   • Implement as a single function in my_solution.py (user) and solution.py (golden).
4. Write tests:
   • Include edge cases and one randomized property check (if applicable).
5. (Optional) Use the paper’s code repo:
   • If the paper links code, clone it under $HUMAN_MATERIAL_PATH/.references/repos/.
   • Read it for correctness and for test cases; do not copy large chunks verbatim.

Modeling exercise workflow

1. Locate the modeling logic:
   • The key formula(s), scaling law(s), or performance reasoning in the paper.
2. Turn it into 3–6 questions:
   • Use numbers so the learner can compute concrete outputs.
   • Include at least one “interpret the result” question.
3. Provide golden answers + explanations:
   • answers.json for numeric targets
   • SOLUTION.md for step-by-step reasoning
4. Add a checker:
   • Compare my_answers.json against answers.json with tolerances.

Local answer-checking mini-skills

The scaffold creates two local mini-skills under:

• $HUMAN_MATERIAL_PATH/exercises/<paper_slug>/skills/uv-check-programming/
• $HUMAN_MATERIAL_PATH/exercises/<paper_slug>/skills/uv-check-modeling/

Use them to:

• Run checks
• Print diffs / failed tests
• Reveal golden solutions + explanations when asked

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