opentelemetry-llm

# OpenTelemetry LLM Skill ## Capabilities - Configure OpenTelemetry SDK for LLM apps - Implement LLM-specific instrumentation - Set up trace exporters (Jaeger, OTLP) - Design semantic conventions for LLM - Configure span attributes for AI workloads - Implement context propagation ## Target Processes - llm-observability-monitoring - agent-deployment-pipeline ## Implementation Details ### Core Components 1. **TracerProvider**: SDK configuration 2. **SpanProcessor**: Batch/simple processors 3. **Exporters**: Jaeger, OTLP, Console 4. **Instrumentation**: Auto and manual ### LLM Semantic Conventions - gen_ai.system (OpenAI, Anthropic) - gen_ai.request.model - gen_ai.request.max_tokens - gen_ai.response.finish_reason - gen_ai.usage.prompt_tokens ### Configuration Options - Exporter selection - Sampling strategies - Resource attributes - Span limits - Context propagation ### Best Practices - Consistent attribute naming - Appropriate sampling - Error handling traces - Propagate context across services ### Dependencies - opentelemetry-sdk - opentelemetry-exporter-* - openinference (optional)