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Scored across 11 tools
Most tools target distinct artifacts in the optimization workflow, but execute_model_code and execute_pyscipopt_sandbox both run PySCIPOpt code in a sandbox without clearly distinguishing their intended use. decompose_optimization_query also overlaps in an advisory role with clarify_requirements, creating some misselection risk.
All tool names use consistent snake_case with a clear verb_noun pattern (review_*, execute_*, formulate_*, etc.). The naming is predictable and readable throughout.
Eleven tools is a reasonable size for a multi-stage optimization modeling workflow covering clarification, formulation, code generation, execution, and review. However, the two execution tools are likely redundant, making the set slightly larger than necessary.
The tool surface covers the end-to-end lifecycle from requirements clarification through math modeling, code generation, execution, and review at each stage. Minor gaps exist, such as tools for solution interpretation/reporting or model persistence, but core workflows are well supported.