Skill UI

Guide for instrumenting LangChain applications with LangSmith tracing, Prometheus metrics, OpenTelemetry spans, structured logging, Grafana dashboards, and alerting to monitor health and performance in staging or production.

Instrument Mistral AI clients, expose Prometheus metrics, configure alerts, and build Grafana dashboards to keep API usage, latency, cost, and errors in check.

Monitor and analyze Windows Management Instrumentation event subscriptions (filters, consumers, bindings) to detect and investigate fileless persistence mechanisms and attacker activity triggered via WMI, especially when other persistence traces are absent.

Builds an eval-driven QA pipeline for Python LLM apps, instrumenting execution, inserting controlled inputs, running pixie test to score responses via evaluators, and iterating on failures to ensure quality.

Guides hooking Phoenix AI services with OpenInference tracing, covering setup, spans, instrumentation, and production deployment for LLM workflows using Python or TypeScript.

A logging wrapper designed to instrument and monitor calls to the Claude API. It automatically tracks critical metrics including token usage, API latency, estimated cost, and error details. Essential for implementing robust observability patterns and setting up proactive alerts in production environments.