Skill UI

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.

This skill provides comprehensive deployment scaffolding for Miro REST API v2 integrations. It manages the entire lifecycle, including setting up OAuth 2.0 authentication, handling incoming webhooks, and ensuring continuous health monitoring. It supports deployment across major cloud platforms like Vercel, Fly.io, and Google Cloud Run, simplifying complex multi-environment SaaS application setups.

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 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.

A comprehensive go-live checklist for deploying SalesLoft API integrations. It covers essential operational aspects including robust authentication, detailed error handling (401, 429, 5xx), rate limit management, health monitoring setup, data integrity checks (idempotency), and mandatory rollback procedures to ensure reliable production operation.

This module provides the core `Logger` abstraction for structured logging within the Webiny API context. It supports multiple logging levels (e.g., debug, info, warn, error), ensuring that developers can record application events and operational data systematically. Using this abstraction helps in centralized logging, which is crucial for debugging, monitoring, and maintaining system health.

A specialized Codex CLI alias designed to check the operational status of the PUA agent or team. This tool reports current active states, corresponding Process IDs (PID), Time To Live (TTL), and identifies stale or inactive records. It is primarily used for system debugging and monitoring agent health via the command line.

This guide helps define a complete observability stack for any service. It systematically covers the Four Golden Signals (latency, traffic, errors, saturation), guiding users to define core metrics, set Service Level Objectives (SLOs), configure actionable alerting rules, and structure comprehensive monitoring dashboards. Essential for establishing robust SRE practices and documenting system health standards.

Utilize this skill to assess the health, adoption, and performance metrics of published EAS Updates directly via the CLI. It reports critical data points including crash rates, unique user counts, install volumes, payload size, and the split between embedded and OTA users, making it essential for post-publish monitoring and regression detection.

This skill integrates with Monte Carlo's observability platform to provide a comprehensive health report for data assets. It checks critical metrics including data freshness, active alerts, monitoring coverage, asset importance, and the health of upstream dependencies. Activates when users inquire about the status, reliability, or quality of a data table.

This skill monitors for regressions on deployed URLs following deployments, merges, or dependency upgrades. It performs comprehensive checks including HTTP status, console errors, network failures, performance metrics (LCP/CLS/INP), and crucial API endpoint health, ensuring service stability in production or staging environments. Supports quick checks, continuous monitoring, and differential comparison against baselines.

This composite CI gate runs four critical cost monitoring checks—budget, burn, anomaly, and projection—in parallel. It surfaces a single, combined health status by taking the maximum exit code. This tool is an operational entry point for integrating comprehensive resource spending alerts directly into CI/CD pipelines, ensuring that resource usage remains within defined boundaries and predicts potential budget overruns.