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Skill
/opentelemetry-llm
OpenTelemetry instrumentation for LLM applications with distributed tracing
Install
$ npx -y skills add a5c-ai/babysitter --skill opentelemetry-llm --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/opentelemetry-llm
Context preview
The summary Claude sees to decide when to auto-load this skill.
OpenTelemetry instrumentation for LLM applications with distributed tracing
SKILL.md
opentelemetry-llm.SKILL.mdname: opentelemetry-llm
description: OpenTelemetry instrumentation for LLM applications with distributed tracing
allowed-tools:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
graph:
domains: [domain:software-engineering]
specializations: [specialization:ai-agents-conversational]
skillAreas: [skill-area:agent-debugging-logging, skill-area:observability-instrumentation]
roles: [role:ml-engineer, role:backend-engineer]
workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
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)
Read more
name: opentelemetry-llm description: OpenTelemetry instrumentation for LLM applications with distributed tracing allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:agent-debugging-logging, skill-area:observability-instrumentation] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
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)
Ships withbabysitter
Enforce obedience on agentic workforces. Manage extremely complex workflows through deterministic, hallucination-free self-orchestration.
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Maintenance
JavaScript
Language
MIT
License
10d ago
Last commit
8mo ago
Created
Repo: a5c-ai/babysitter
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