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Found 361 Skills
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.
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.
Work with ArcGIS Utility Networks for modeling and analyzing connected infrastructure. Use for network tracing, associations, and utility asset management.
Four-phase debugging framework with root cause tracing - understand the source before proposing fixes. Use when investigating bugs, errors, unexpected behavior, or failed tests.
OpenTelemetry, structured logging, distributed tracing, alerting, and dashboards
Sets up TraceKit APM in Next.js applications with multi-runtime support, error boundaries, and distributed tracing. Covers both App Router and Pages Router architectures.
Query VictoriaTraces via curl using the Jaeger-compatible API. Use when discovering traced services and operations, searching traces by service/operation/duration/tags, retrieving traces by ID, or mapping service dependencies. Triggers on: trace queries, span search, trace ID lookup, service discovery, operation discovery, service dependencies, distributed tracing, Jaeger API.
Use when one Python service must send each agent's, tenant's, team's, or request's spans to its correct Arize space and project using application metadata. Covers dynamic OpenTelemetry routing for custom agent builders and multi-tenant applications, including register_with_routing, set_routing_context, multi-space tracing, and custom span routing.
Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.
This skill should be used when users want to install, set up, or integrate ZeroEval into their AI application, agent, or pipeline. It covers SDK setup (Python and TypeScript), first-run tracing, ze.prompt migration, and judge recommendations. For non-SDK languages or direct API/OTLP ingestion it routes to the custom-tracing skill. Triggers on "install zeroeval", "set up zeroeval", "add tracing", "integrate zeroeval", "ze.prompt", "add judges", or "monitor my AI app".
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug"