review-problem

You validate optimization problem files by running automated static and dynamic analysis across the three associated files to ensure structural agreement and constraint accuracy. The review-problem Skill checks ADNLPProblems, PureJuMP, and Meta files to verify mathematical programming consistency.

Automated code review for mathematical programming problems is the process of auditing optimization files to detect structural mismatches and constraint errors. This Skill cross-references the ADNLPProblems, PureJuMP, and Meta files to confirm they all agree on the problem's definition.

Yes, static and dynamic analysis capabilities are required to review optimization problems. The Skill relies on both analysis methods to comprehensively verify the correctness and consistency of the three associated mathematical programming files during the review process.

Yes, you can check ADNLPProblems and PureJuMP files together with the Meta file. The Skill performs a problem-specific analysis across all three associated files to confirm they agree on the optimization problem's structure and constraints.

The best way to check that three optimization files agree is to run a comprehensive automated review that cross-validates the ADNLPProblems, PureJuMP, and Meta files. This ensures all three files consistently define the mathematical programming problem's structure and constraints.