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langsmith-trace

Trace and query AI application executions via LangSmith CLI.

1|Updated Dec 22, 2025
Search Tags:#debugging#monitoring#cli#llm#tracing#langsmith
One-click install
npx skills add https://github.com/dhar174/langgraph_system_generator --skill langsmith-trace-dhar174
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langsmith-trace
Source: https://github.com/dhar174/langgraph_system_generator/tree/main/.github/skills/langsmith-trace
Command: npx skills add https://github.com/dhar174/langgraph_system_generator --skill langsmith-trace-dhar174

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you understand and debug your AI applications by providing tools to trace their execution and query historical data.

Core Features & Use Cases

  • Add Tracing: Integrate LangSmith tracing into your LangChain/LangGraph applications or other frameworks using Python/TypeScript.
  • Query Traces: Use the langsmith CLI to list, get, and export trace data for analysis.
  • Use Case: Debug a failing LLM call by querying its trace to inspect inputs, outputs, and intermediate steps.

Quick Start

Use the langsmith trace skill to list the last 10 traces in your default project.

Frequently Asked Questions about langsmith-trace

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug a failing LLM call by inspecting inputs and intermediate steps?▼

To debug a failing LLM call, you query its execution trace to inspect inputs, outputs, and intermediate steps using the LangSmith CLI. This facilitates analysis of application performance and error identification.

Can I add tracing to LangChain and LangGraph applications using Python?▼

Yes, you can add tracing to LangChain and LangGraph applications using Python and TypeScript. This integration enables comprehensive monitoring and debugging of AI applications through detailed execution tracing.

How do I list and export trace data for AI application monitoring?▼

You list and export trace data for AI application monitoring by using the langsmith CLI. The CLI allows you to list the last 10 traces in your default project, get specific trace details, and export data for further review.

Does LangSmith tracing work with frameworks outside of LangChain?▼

LangSmith tracing works with other frameworks beyond LangChain and LangGraph. It supports integration with various frameworks using Python and TypeScript to facilitate comprehensive monitoring and debugging of AI applications.

What is the best way to monitor AI application performance and identify errors?▼

The best way to monitor AI application performance and identify errors is through detailed execution tracing. By integrating LangSmith tracing, you can query historical data to analyze performance and inspect intermediate steps for failures.

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