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Found 218 Skills
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
Instrumenting Go applications with OpenTelemetry for distributed tracing, Prometheus for metrics, and structured logging with slog
Use when building cloud-native apps. Keywords: kubernetes, k8s, docker, container, grpc, tonic, microservice, service mesh, observability, tracing, metrics, health check, cloud, deployment, 云原生, 微服务, 容器
Axum (Rust) web framework patterns for production APIs: routers/extractors, state, middleware, error handling, tracing, graceful shutdown, and testing
Observability and SRE expert. Use when setting up monitoring, logging, tracing, defining SLOs, or managing incidents. Covers Prometheus, Grafana, OpenTelemetry, and incident response best practices.
Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.
MUST READ before setting up observability for ADK agents or when analyzing production traffic, debugging agent behavior, or improving agent performance. ADK observability guide — Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations, and troubleshooting. Use when configuring monitoring, tracing, or logging for agents, or when understanding how a deployed agent handles real traffic.
Use this skill when designing backend systems, databases, APIs, or services. Triggers on schema design, database migrations, indexing strategies, distributed systems architecture, microservices, caching, message queues, observability setup, logging, metrics, tracing, SLO/SLI definition, performance optimization, query tuning, security hardening, authentication, authorization, API design (REST, GraphQL, gRPC), rate limiting, pagination, and failure handling patterns. Acts as a senior backend engineering advisor for mid-level engineers leveling up.
Complete reference for the Galileo AI platform Python SDK for evaluating, observing, and protecting GenAI applications. Use when building Python applications that need LLM evaluation, production observability, tracing, or runtime guardrails with Galileo.
Enforces consistent structured logging with request correlation IDs, standardized log schema, middleware integration, and best practices. Use for "structured logging", "log standardization", "request tracing", or "log correlation".
Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging
Set up comprehensive observability for Groq integrations with metrics, traces, and alerts. Use when implementing monitoring for Groq operations, setting up dashboards, or configuring alerting for Groq integration health. Trigger with phrases like "groq monitoring", "groq metrics", "groq observability", "monitor groq", "groq alerts", "groq tracing".