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Found 356 Skills
Adds tracing, telemetry, and observability to an assistant-ui backend. Use when wiring an AI SDK route handler (streamText/generateText, toUIMessageStreamResponse) to a tracing backend: Langfuse via OpenTelemetry (LangfuseSpanProcessor and NodeSDK in instrumentation.ts, experimental_telemetry isEnabled, propagateAttributes with traceName/userId/sessionId, langfuseSpanProcessor.forceFlush on serverless), LangSmith via wrapAISDK(ai) from langsmith/experimental/vercel (createLangSmithProviderOptions, awaitPendingTraceBatches), or Helicone via createOpenAI baseURL https://oai.helicone.ai/v1 with the Helicone-Auth header. Also covers rendering collected spans with @assistant-ui/react-o11y headless primitives (SpanResource, SpanPrimitive Root/Indent/CollapseToggle/StatusIndicator/TypeBadge/Name/Children, SpanByIndexProvider, SpanData/SpanState) mounted via useAui/AuiProvider from @assistant-ui/store. Use for missing or empty traces, edge vs nodejs runtime telemetry, serverless flush issues, or trace waterfalls.
Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Use this skill when working on infrastructure, DevOps, CI/CD, Kubernetes, cloud deployment, observability, or cost optimization. Activates on mentions of Kubernetes, Docker, Terraform, Pulumi, OpenTofu, GitOps, Argo CD, Flux, CI/CD, GitHub Actions, observability, OpenTelemetry, Prometheus, Grafana, AWS, GCP, Azure, infrastructure as code, platform engineering, FinOps, or cloud costs.
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
Use this skill when working with SigNoz - open-source observability platform for application monitoring, distributed tracing, log management, metrics, alerts, and dashboards. Triggers on SigNoz setup, OpenTelemetry instrumentation for SigNoz, sending traces/logs/metrics to SigNoz, creating SigNoz dashboards, configuring SigNoz alerts, exception monitoring, and migrating from Datadog/Grafana/New Relic to SigNoz.
Build and operate modern Node.js applications with strong architecture, dependency hygiene, performance, resilience, observability, and security controls. Use when designing project layout, runtime/module strategy, testing and CI, release workflows, and production operations.
Query and troubleshoot logs in Alibaba Cloud Log Service (SLS) using query|analysis syntax and the Python SDK. Use for time-bounded log search, error investigation, and root-cause analysis workflows.
Use when setting up metrics, alarms, or troubleshooting missing data in OCI Monitoring. Covers metric namespace confusion, alarm threshold gotchas, log collection setup, and common monitoring gaps.
Use when working with error diagnostics smart debug
Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations. Supports dashboard creation, updates, data extraction, structure analysis, and best practices.
Exclusive skill set for the GoFrame development framework. Provides comprehensive framework usage guidelines for Go language developers, covering best practices for core components such as command-line management, configuration management, logging components, error handling, data validation, type conversion, cache management, template engines, database ORM, and I18n internationalization. Includes project engineering structure specifications, development mode guidelines, common problem solutions, and rich practical code examples. Suitable for building various Go projects such as RESTful APIs, gRPC microservices, web applications, and CLI tools, helping developers quickly master GoFrame framework features, improve development efficiency and code quality.