Skill UI

Aggregates performance metrics from applications, systems, databases, caches, queues, and external services into a central platform, helping teams define a consistent taxonomy, choose aggregation tools, and create dashboards and alerts for faster monitoring and troubleshooting.

A comprehensive Python SDK for interacting with Azure Monitor services. It enables developers to execute complex Kusto Query Language (KQL) queries against Log Analytics workspaces and retrieve various resource metrics (CPU usage, network traffic, etc.). Ideal for building robust monitoring dashboards, automated alerting systems, and custom data analysis pipelines in cloud environments.

A comprehensive SDK suite for implementing real-time messaging and pub/sub patterns using Azure Web PubSub with TypeScript. It utilizes WebSocket connections to facilitate robust communication, supporting features like group broadcasts, direct user messaging, and custom event handling. Ideal for building chat applications, live dashboards, and notification systems requiring high real-time performance.

Provides a comprehensive guide and implementation pattern for building scalable WebSocket servers. This skill covers real-time, bidirectional communication, handling connection lifecycle, implementing room/channel subscriptions, and ensuring horizontal scalability using Redis pub/sub. It is ideal for developing high-throughput, low-latency applications like chat platforms, live dashboards, and collaborative editing tools.

Monitor the effectiveness and adoption of AI code reviews using CodeRabbit. This skill calculates critical metrics including review coverage percentage, time-to-first-review, and comment acceptance rates. It is ideal for building organizational dashboards to maintain high code quality and optimize development workflows.

Automates configuring and aggregating infrastructure metrics across compute, storage, network, containers, load balancers, and databases with Prometheus, Datadog, or CloudWatch for dashboards and capacity tracking.

Automates crafting APM dashboards by identifying required metrics, selecting golden signals, and generating configurations for Grafana, Datadog, or other monitoring platforms, so you can quickly visualize application health and performance.

This skill provides a comprehensive solution for implementing observability for Customer.io integrations. It covers setting up Prometheus metrics (latency, request counts, bounces), structured JSON logging with PII redaction, and OpenTelemetry tracing. Use it when building robust, production-grade monitoring dashboards and alerting systems for Customer.io APIs.

This skill models the expertise of a senior data scientist, covering the entire data science lifecycle. It provides advanced capabilities in statistical modeling, machine learning (deep learning, XGBoost), predictive analytics, and business intelligence. From raw data exploration (EDA) to deploying production-ready models and creating actionable dashboards, it covers technical depth across Python, R, SQL, and cloud platforms, while applying domain knowledge in finance, marketing, and operations.

This skill provides comprehensive observability for the Databricks platform. It enables users to monitor job run histories, track cluster utilization and associated costs (DBU), detect slow SQL queries, and audit access logs. Use it for setting up robust monitoring dashboards, ensuring pipeline health, and optimizing resource consumption across the entire data stack.

Automates Datadog monitoring workflows via Composio’s Rube MCP, letting you query metrics, search logs, manage monitors and dashboards, and create events or downtimes after connecting to the MCP toolkit and tools list.

Guides teams through discovery, research, moodboards, palettes, typography, and Tailwind-ready code so they can ship distinctive, accessible front-end experiences with process validation.