LLM Tracing and Observability Setup
CommunityInstrument LLM apps with end-to-end tracing.
AuthorNotysoty
Version1.0.0
Installs0
System Documentation
What problem does it solve?
End-to-end observability for LLM pipelines enables you to see prompts, model responses, tool calls, latency, and costs, eliminating blind debugging and guesswork.
Core Features & Use Cases
- Backend-agnostic tracing setup supporting LangSmith, Langfuse, Helicone, and OpenTelemetry.
- Automatic, structured tracing of LLM calls, prompts, model outputs, and token counts, plus tool calls and retrieval steps.
- Easy integration with LangChain and other LLM stacks in Python or TypeScript, with guidance for instrumentation and metadata tagging.
- Production-readiness guidance including metrics to monitor and steps for adding custom spans and user feedback.
Quick Start
Copy this file to .agents/skills/llm-tracing-setup/SKILL.md in your project root and follow the prompts to enable end-to-end LLM observability with your chosen tracing backend.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: LLM Tracing and Observability Setup Download link: https://github.com/Notysoty/openagentskills/archive/main.zip#llm-tracing-and-observability-setup Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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