Skill UI

This skill guides the definition of comprehensive API contracts, serving as the shared interface specification between backend and frontend services. It covers defining request/response schemas, endpoint routes, TypeScript interfaces, and standardized error handling. Use it when establishing, modifying, or documenting the interaction points between different system components to ensure seamless integration and type consistency.

This skill guides the definition of comprehensive API contracts, serving as the shared interface specification between backend and frontend services. It covers defining request/response schemas, endpoint routes, TypeScript interfaces, and standardized error handling. Use it when establishing, modifying, or documenting the interaction points between different system components to ensure seamless integration and type consistency.

This SDK provides a comprehensive client library for Azure AI Document Translation service. It enables large-scale, batch translation of various document formats, including Word, PDF, Excel, and PowerPoint, while accurately preserving the original document structure and formatting. It supports features like glossary integration and async operations, making it ideal for enterprise content localization pipelines.

This SDK provides a comprehensive client library for Azure AI Document Translation service. It enables large-scale, batch translation of various document formats, including Word, PDF, Excel, and PowerPoint, while accurately preserving the original document structure and formatting. It supports features like glossary integration and async operations, making it ideal for enterprise content localization pipelines.

Automates Azure ML Deployer workflows by offering best-practice guidance, code/config generation, and validation for serving, MLOps pipelines, monitoring, and production optimization.

Automates Azure ML Deployer workflows by offering best-practice guidance, code/config generation, and validation for serving, MLOps pipelines, monitoring, and production optimization.

Provides automated guidance for setting up canary deployments in ML production environments, covering model serving, MLOps pipelines, monitoring, and configuration validation.

This skill details the architecture and implementation of a robust API Gateway, serving as the single entry point for multiple backend microservices. It centrally manages critical cross-cutting concerns, including path-based and header-based routing, JWT/OAuth2 authentication, rate limiting, load balancing, and circuit breaker protection. This pattern is essential for building resilient, scalable, and maintainable microservices architectures, significantly simplifying client integration and request management.

Framework for improving existing marketing copy through seven sequential sweeps that check clarity, voice, benefits, evidence, specificity, and more while preserving the original message and brand tone.

This guide outlines the complete MLOps workflow on Databricks. It covers feature engineering using Feature Store, tracking experiments with MLflow, managing model versions in the Model Registry, and deploying real-time inference endpoints via Mosaic AI Model Serving. Ideal for building robust, production-grade ML pipelines.

Automate Datarobot operations via Composio's Rube MCP by discovering tool schemas, managing connections, and executing workflows with RUBE_MULTI_EXECUTE_TOOL while observing schema compliance and session reuse best practices.

Deploying Machine Learning Models automates serving trained models to production by analyzing requirements, generating API and infrastructure code, and orchestrating deployment workflows with validation, error handling, and monitoring baked in.