my_awesome_copilot

Implement Marketing Mix Models (MMM) using the pymc-marketing Bayesian library. Covers model setup, adstock/saturation transformations, fitting, diagnostics, budget allocation, lift test calibration, causal inference, and model evaluation. Use when building or improving MMM models with pymc-marketing, navigating pymc-marketing documentation, choosing the right MMM notebook or API reference, or answering any pymc-marketing MMM implementation question. Combine with the pymc-modeling skill for advanced Bayesian modeling questions.

Complete workflow for creating Agent Skills following the open standard. Use when building new capabilities, setting up skill directories, or designing progressive loading workflows for VSCode Copilot customization.

Complete VSCode Copilot asset management system with intelligent discovery, installation, and deployment capabilities for agents, prompts, instructions, collections, and skill packages.