Skill UI

This skill provides robust patterns for handling API rate limits and throttling, specifically demonstrated using the Lokalise API. It teaches how to implement request queuing (p-queue) with required spacing, automatic exponential backoff with jitter upon receiving 429 errors, and how to proactively monitor and utilize rate limit headers (X-RateLimit-*). Ideal for optimizing high-throughput, reliable API interactions and bulk operations.

This skill provides a comprehensive guide to implementing observability for MaintainX API integrations. It covers best practices for structured logging, Prometheus metrics collection (Counters, Histograms, Gauges), API request tracing using Axios interceptors, and setting up health and alerting endpoints. Use this when you need to monitor API reliability, detect performance degradation, and ensure rapid issue detection in your connected services.

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

This guide provides comprehensive, step-by-step instructions for installing and configuring the Manifest observability plugin for your AI agent. Users can use this skill to set up telemetry, connect the agent to Manifest for real-time monitoring, manage API keys, and troubleshoot various connection issues, ensuring full system observability.

Enables Claude to monitor and analyze application CPU usage, detect hotspots, inefficient loops and regexes, and offer optimization strategies such as asynchronous processing or algorithmic improvements to boost performance.

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.

Delivers end-to-end monitoring setups—structured logging, Prometheus/Grafana dashboards, alerting rules, distributed tracing, and load/profile testing—so teams can observe services, debug production issues, and plan capacity.

Documents setting up OpenTelemetry tracing/metrics, Prometheus/Grafana monitoring, structured logging, and alerting rules so teams can instrument services, track performance, and respond to incidents.

Guides performance testing teams through network latency tester tasks by suggesting best practices, generating production-ready scripts/configs, and validating results across load, stress, benchmarking, and monitoring scenarios.

Automates New Relic observability workflows through the Composio MCP integration, letting teams list and manage alert policies, conditions, channels, and monitored applications from a single toolkit.