Skill UI

Automates creating and validating GCP BigQuery views with best-practice guidance, production-ready code snippets, and integrations for Vertex AI, Cloud Run, Firebase, and similar services to keep analytics workloads consistent.

Guides TensorFlow Serving setup with step-by-step ML deployment orchestration, enforcing best practices, ready-to-run configurations, and output validation for production inference services.

Guides multi-location retailers through demand forecasting, safety stock calculation, replenishment planning, promotional lift estimation, and ABC/XYZ segmentation, blending statistical best practices with ML-ready feature engineering to balance service levels and inventory costs.

BioServices provides Python wrappers for 40+ bioinformatics services, allowing cross-database queries, identifier mapping, pathway exploration, and sequence or compound research within consistent workflows.

FlowIO reads and writes Flow Cytometry Standard (FCS) files, exposing metadata, channels, and NumPy event arrays while allowing CSV/DataFrame conversion, making it ideal for cytometry pipelines and backend preprocessing services.

Query the Reactome Content and Analysis Services (or the reactome2py client) to fetch pathway hierarchies, map genes, run overrepresentation/expression analyses, and explore disease interactions for systems biology research.

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It is designed for modeling complex systems where entities interact with shared resources and time-based events occur, such as manufacturing lines, service queues, network traffic, or logistics networks. Use this skill to analyze resource contention, simulate process optimization, conduct capacity planning, and model dynamic system behaviors.