# Opentelemetry LLM

> Opentelemetry LLM is an Agent Skill for devops & security published in the a5c-ai/babysitter repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

OpenTelemetry instrumentation for LLM applications with distributed tracing

- Skill name: `opentelemetry-llm`
- Category: [DevOps & Security](https://www.openparable.com/skill/devops-security/1)
- Source: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/ai-agents-conversational/skills/opentelemetry-llm/SKILL.md
- Repository: a5c-ai/babysitter (1,548 GitHub stars when collected)

## SKILL.md

# 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)

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Source: https://www.openparable.com/skill/devops-security/opentelemetry-llm (OpenParable). Cite the canonical URL above.