Agent Observability Setup

$2.99Official

Implement tracing, logging, and monitoring for AI agent systems: LLM call traces, tool execution logs, latency tracking, and replay debugging.

agent-infrastructureobservabilitytracingloggingmonitoringdebuggingagents· v1· by SkillingMain
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Model requirements

Capability tier

advanced

Min context window

33k tokens

Recommended models
Claude Sonnet 4GPT-4o-miniGemini 2.5 FlashLlama 3.3 70B (self-hosted)Qwen 2.5 72B (self-hosted)Mistral Large

Preview

When to use

Use this skill when the user needs visibility into what an AI agent is doing: "I can't tell why my agent made that decision," "add tracing," "debug a failed agent run," "set up monitoring for our agent system." Trigger phrases: observability, tracing, agent traces, LLM monitoring, replay debugging, agent logs, LangSmith, OpenTelemetry.

Do NOT use it for application logging in general (use standard APM), or for evals (related but distinct — observability is recording; evals are measuring). Use this when the specific challenge is the opacity of multi-step, tool-calling agent behavior.

Inputs to gather

  1. The agent system: framework (LangGraph, CrewAI, raw function-cal

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