OpenTelemetry LLM Skill

SkillMonitoring & ops

OpenTelemetry instrumentation for LLM applications with distributed tracing

Use OpenTelemetry LLM Skill in Claude, ChatGPT or Ahel Desktop

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Then ask your AI: use the OpenTelemetry LLM Skill skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

No other account needed.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

OpenTelemetry LLM SkillStart free

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/opentelemetry-llm/SKILL.md and read by ahel’s review.

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

TracerProvider: SDK configuration
SpanProcessor: Batch/simple processors
Exporters: Jaeger, OTLP, Console
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)

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: opentelemetry-llm
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter