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Found 333 Skills
See exactly what your AI did on a specific request. Use when you need to debug a wrong answer, trace a specific AI request, profile slow AI pipelines, find which step failed, inspect LM calls, view token usage per request, build audit trails, or understand why a customer got a bad response. Covers DSPy inspection, per-step tracing, OpenTelemetry instrumentation, and trace viewer setup.
Comprehensive guide and toolkit for diagnosing Rspack build issues. Quickly identify where crashes/errors occur, or perform detailed performance profiling to resolve bottlenecks. Use when the user encounters build failures, slow builds, or wants to optimize Rspack performance.
Add LangWatch tracing and observability to your code. Use for both onboarding (instrument an entire codebase) and targeted operations (add tracing to a specific function or module). Supports Python and TypeScript with all major frameworks.
Setup Sentry Tracing (Performance Monitoring) in any project. Use this when asked to add performance monitoring, enable tracing, track transactions/spans, or instrument application performance. Supports JavaScript, TypeScript, Python, Ruby, React, Next.js, and Node.js.
Instruments Python and TypeScript code with MLflow Tracing for observability. Triggers on questions about adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, or tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen). Examples - "How do I add tracing?", "How to instrument my agent?", "How to trace my LangChain app?", "Getting started with MLflow tracing", "Trace my TypeScript app"
Implement distributed tracing using logs, including trace context propagation, span logging, correlation IDs, and OpenTelemetry integration for observability
Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
Generate EventSettings metadata to enable or disable Platform Tracing (TraceSpanEvent publishing) in Event Monitoring. Use this skill for any EventSettings enablePlatformTracing metadata work. TRIGGER when: user mentions Platform Tracing, TraceSpanEvent, enable tracing in Event Monitoring Settings, event monitoring tracing toggle, enablePlatformTracing, .settings-meta.xml for Event settings tracing, turn on trace span events, or stop publishing trace spans. DO NOT TRIGGER when: user wants Agentforce agent tracing to Data Cloud (use platform-tracing-agentforce-configure), wants Event Log Files or ELF generation, wants Change Data Capture (use integration-eventing-cdc-configure), or wants ManagedEventSubscription (use integration-eventing-subscription-configure).
Generate AgentforcePlatformTracingSettings metadata to enable or disable Agentforce agent execution trace spans flowing to Data Cloud. Use this skill for any AgentforcePlatformTracingSettings metadata work. TRIGGER when: user mentions Agentforce tracing, agent trace spans, Data Cloud tracing, AgentforcePlatformTracingSettings, platform observability tracing, enable agent tracing, wants agent execution spans in Data Cloud, mentions .settings-meta.xml for AgentforcePlatformTracing, or asks about enabling observability for Agentforce agents. DO NOT TRIGGER when: user wants Platform Tracing for TraceSpanEvent (use platform-tracing-configure), wants to query or analyze existing agent trace data in Data Cloud (use agentforce-observe), wants Event Log Files or ELF configuration, wants Change Data Capture (use integration-eventing-cdc-configure), or wants ManagedEventSubscription (use integration-eventing-subscription-configure).
Implement distributed tracing with Jaeger and Zipkin for tracking requests across microservices. Use when debugging distributed systems, tracking request flows, or analyzing service performance.
Implement distributed tracing with correlation IDs, trace propagation, and span tracking across microservices. Use when debugging distributed systems, monitoring request flows, or implementing observability.
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior