Purpose

Generate Python modeling code from a validated candidate method pool and cleaned data.

This skill implements the approved candidate methods (baseline, main candidates, optional improved) as Python scripts. It should produce code that reads cleaned data, runs the planned models, saves results in the experiments/roundN/ output structure, generates a run_summary.json, and produces portable artifacts for downstream experiment reports, robustness checks, and paper writing.

This skill does not choose the model, clean raw data, review code, run final QA, or write paper sections.

When to use

Use this skill:

• After model-code-analyzer hands off to python-model-code-generator.
• When implementation.target = python.
• When Python is allowed by the contest or requested by the user.
• When the candidate method pool and cleaned data are ready.
• When executable .py scripts are needed for one or more candidate methods in a specific experiment round.

Preconditions