Skill UI

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.

Automate deploying production-ready monitoring stacks like Prometheus, Grafana, and Datadog, delivering configuration files, deployment scripts, and guided instructions for infrastructure-focused observability setups.

A comprehensive toolkit for monitoring the health and performance of Fireflies.ai integration. It tracks crucial metrics such as API connectivity, webhook delivery status, transcript processing latency, and seat utilization. Built using Prometheus metrics and suitable for Grafana dashboards, ensuring reliable data pipeline monitoring for engineering teams.

Guides teams through selecting a RUM platform, defining Core Web Vitals and custom events, and wiring JavaScript instrumentation so actual user performance data can be collected and analyzed for web apps.

This guide provides comprehensive metrics, instrumentation code (TypeScript), health check logic, and alerting rules for monitoring a SaaS platform like Juicebox. It covers critical metrics such as search latency (p95), data ingestion rates, API error rates, and quota usage, ensuring the maintenance of an optimal user experience and data integrity. Use this to establish robust operational monitoring dashboards and alerts.

This comprehensive checklist guides the operational validation of the Juicebox AI talent search and analysis platform in a production environment. It ensures system reliability, data security, and service continuity by reviewing critical areas such as API key management, rate limit handling, robust error detection (circuit breakers, exponential backoff), data encryption (GDPR/CCPA compliance), and comprehensive monitoring setup. It is essential for preventing service failures and maintaining search data integrity.

Automates database replication tasks with the database-replication-manager plugin, covering setup, failover, lag monitoring, and read scaling for PostgreSQL/MySQL clusters.

Monitors PostgreSQL and MySQL health with real-time metrics, predictive alerts, and automated remediation, letting you preempt bottlenecks and respond to production issues quickly.

Enables Claude to monitor database transactions with the database-transaction-monitor plugin, detect long-running operations, lock contention, and rollback spikes, and streamline response through the `/txn-monitor` command.

Automates comprehensive monitoring and alerting of HTTP, database, API, background job, and client errors so teams can track, analyze, and resolve reliability issues before they impact users.

This skill provides comprehensive guidelines and optimization strategies for managing API usage and reducing costs when interacting with OpenEvidence. It covers best practices such as implementing caching, batching requests, selecting appropriate API tiers, and monitoring usage dashboards to ensure efficient and cost-effective data retrieval in healthcare applications.