mcm-c-modeler

What problem does it solve?

This Skill provides a structured framework to interpret COMAP MCM/ICM Problem C by translating the prompt into a modular data-analytic workflow: problem decomposition, data auditing, and principled modeling with uncertainty and robustness assessment.

Core Features & Use Cases

• Data audit and inventory extraction: identify available data, missingness, and data quality issues; list attachments and time ranges; understand data dictionaries.
• Modular modeling plan: split the task into 2-4 deliverable models with clear inputs/outputs and evaluation criteria.
• Baseline and improved modeling with uncertainty: propose an interpretable baseline and enhanced models with uncertainty intervals and robustness checks for decision support.
• Documentation-driven reproducibility: maintain a traceable pipeline and produce auditable outputs for reporting.
• Use Case: apply to a COMAP MCM C problem by confirming data sufficiency, selecting feasible external data, and producing validated risk/uncertainty results.

Quick Start

Run the full modeling workflow on the provided data to generate a baseline and an improved, explainable model with uncertainty analysis.