Skill UI

A portable, framework-agnostic observability system for React and React Native apps. It defines typed event taxonomies, implements non-blocking analytics fan-out, reports real-user Core Web Vitals, and manages user consent. Ensures SSR safety and prevents vendor failures from breaking the application.

Create and manage production-ready Grafana dashboards for comprehensive system observability. Covers dashboard design principles, panel types, variables, alerts, and best practices for monitoring applications, infrastructure, and business metrics.

A comprehensive guide for designing and implementing production-grade microservices using gRPC in Go. Covers best practices for API contract standardization with Protobuf and Buf, securing service-to-service communication via mTLS, and integrating deep observability using OpenTelemetry interceptors. Ideal for building high-performance, reliable internal APIs.

Expert hybrid cloud architect for designing multi-cloud solutions across AWS, Azure, GCP, and private clouds, covering connectivity, security, cost, and observability.

This skill provides expert guidance for Site Reliability Engineering (SRE) incident response. It covers rapid problem resolution, modern observability practices, and comprehensive incident management workflows. Use it for assessing severity, establishing command structures, stabilizing systems, investigating root causes using distributed tracing and metrics, communicating with stakeholders, and conducting blameless post-mortems to improve system resilience.

This skill orchestrates multi-agent incident response workflows following modern SRE practices. It guides detection, triage, investigation, mitigation, and resolution phases to ensure rapid service recovery and learning. Includes severity classification, observability analysis, root cause analysis, and deployment strategies for critical system outages and security breaches.

Investigate production issues, reproduce root causes, implement scoped fixes, and verify recovery using tests and observability. This skill provides a multi-agent orchestration workflow for intelligent issue resolution, leveraging AI debugging tools, observability platforms, and automated root cause analysis to reduce MTTR and prevent future occurrences.

A specialized workflow for deploying applications to Kubernetes, covering container orchestration, Helm charts, service mesh configuration, production-ready K8s patterns, security policies, and observability. Use for cluster deployments, chart creation, mesh setup, networking, and security hardening.

Instrument LLM applications with Langfuse tracing, prompt versioning and evaluation. Covers SDK setup, masking sensitive data, span verification, dataset comparison and debugging production LLM pipelines.

Expert skill for building production-grade AI systems using LangChain 0.1+ and LangGraph. Covers agent architecture, RAG pipelines, memory systems, and deployment strategies. Ideal for developing sophisticated LLM applications with observability and scalability.

Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation. Use when building an always-on private AI inference server on Apple Silicon.

Install and configure the Manifest observability plugin, setting up telemetry, configuring API keys, and troubleshooting integration.