Skill UI

This skill provides comprehensive observability for CoreWeave's GPU-intensive workloads running on Kubernetes. It monitors critical operational metrics, including GPU utilization, memory usage, inference latency (p99), and job completion rates. Use it for setting up DCGM metrics dashboards, configuring proactive alerts for underutilization or Out-Of-Memory (OOM) conditions, and ensuring high reliability for AI/ML deployments.

Provides comprehensive monitoring, metrics tracking, and alerting for all Figma API interactions. It instruments client calls to track key metrics like request latency, error rates, rate limit status, and cache performance. This solution ensures robust operational visibility, allowing developers to maintain high availability and stability for Figma integrations in production environments.

This skill provides a comprehensive observability stack for Flexport logistics integrations. It sets up Prometheus metrics for API health tracking, uses structured logging (pino) for debugging, implements OpenTelemetry tracing for latency analysis, and defines actionable Grafana dashboards and alert rules. This ensures reliable, performant, and fully monitored logistics operations.

This tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

This skill implements comprehensive observability (metrics, logging, and alerting) for Grammarly API integrations. It monitors critical performance indicators such as text check latency (p95), API error rates, suggestion acceptance rates, and token consumption. Use this setup when establishing robust monitoring systems, tracking real-time API performance degradation, or implementing proactive alerting to ensure consistent, high-quality user experiences in writing and editing flows.

This comprehensive skill guides developers on implementing full observability for HubSpot API integrations. It details how to instrument calls using industry-standard tools, including Prometheus metrics (Counters, Histograms, Gauges), OpenTelemetry tracing, structured logging (pino), and configuring AlertManager rules. Use this when needing to monitor CRM integration health, track latency, detect errors, or manage rate limits for mission-critical API operations.

This skill provides a comprehensive guide to setting up full observability for Intercom integrations. It covers implementing Prometheus metrics (counters, histograms, gauges) to track API request status, latency, and error rates. Furthermore, it demonstrates structured logging using Pino and OpenTelemetry tracing, offering deep, actionable insights into integration health. Ideal for DevOps, backend engineering, and robust system monitoring.

Provides comprehensive observability for Miro REST API v2 integrations. It captures critical metrics using Prometheus (request rates, latency, error tracking) and OpenTelemetry traces for end-to-end request flow visibility. Includes structured logging for detailed debugging and robust rate limit management, ensuring your applications are highly reliable and maintainable.

This skill provides a comprehensive framework for setting up robust observability for Navan API integrations in production environments. It guides users through implementing structured logging, tracking request latency, classifying various errors (auth, rate limit, server), and monitoring the OAuth token refresh lifecycle. Includes practical steps and YAML examples for configuring alerts and building dashboards in platforms like Datadog, CloudWatch, or Prometheus/Grafana.

A comprehensive wrapper for Notion API calls that implements full observability. It automatically tracks vital metrics including request rates, latency (average, p95), error counts, and rate limit status. This skill is essential for building reliable monitoring dashboards, setting up alerts, and ensuring the health of Notion integrations in production environments. It supports structured logging and Prometheus metrics.

This skill allows users to programmatically set up a comprehensive observability stack for Oracle Cloud Infrastructure (OCI) resources. It guides the creation of metric queries, alarm rules, custom metric publishing, and detailed log searches using the Python SDK. By automating monitoring and alerting, users gain full control over their infrastructure visibility, eliminating reliance on the OCI Console UI for critical operational checks.

This skill guides the setup of comprehensive observability for Palantir Foundry integrations. It covers structured logging, Prometheus metrics (latency, errors), health checks, and Prometheus alert rules, enabling robust monitoring of API integration health, performance, and reliability. Use this when implementing production-grade monitoring for Foundry APIs.