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langsmith-trace

Query and export LangSmith execution traces to analyze LLM application runs.

8|Updated Jul 26, 2026
Search Tags:#debugging#monitoring#llm#observability#tracing#langsmith
One-click install
npx skills add https://github.com/joonlab/joonlab-claudecode-setting-for-share --skill langsmith-trace-joonlab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langsmith-trace
Source: https://github.com/joonlab/joonlab-claudecode-setting-for-share/tree/main/claude/skills/langsmith-trace
Command: npx skills add https://github.com/joonlab/joonlab-claudecode-setting-for-share --skill langsmith-trace-joonlab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langsmith-cli.

What problem does it solve?

This skill addresses the complexity of debugging and monitoring LLM-powered applications by providing a standardized interface to manage LangSmith traces, runs, and datasets.

Core Features & Use Cases

  • Observability: Easily add tracing to Python or TypeScript applications using decorators and wrapped clients.
  • Analysis: Query, filter, and export trace data to identify performance bottlenecks or failed LLM calls.
  • Use Case: When a RAG pipeline produces unexpected results, use this skill to export the full execution trace hierarchy to analyze the specific retrieval and generation steps.

Quick Start

Use the langsmith trace list command to show the last 10 traces from your current 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 unexpected results in my RAG pipeline using LLM tracing?▼

To debug unexpected RAG pipeline results, use LLM tracing to export the full execution trace hierarchy. This lets you analyze specific retrieval and generation steps to pinpoint performance bottlenecks or failed LLM calls.

How do I add observability and tracing to my LLM applications?▼

Add observability to LLM applications by instrumenting code with decorators and wrapped clients. This facilitates standardized tracing for Python or TypeScript applications to monitor execution runs and manage evaluation datasets.

Do I need the LangSmith CLI to query execution traces?▼

Yes, querying execution traces requires the LangSmith CLI tool and appropriate API key configuration. This setup interfaces directly with the LangSmith platform to list, filter, and export trace data for analysis.

What is the best way to analyze performance bottlenecks in LLM calls?▼

The best way to analyze LLM call bottlenecks is querying, filtering, and exporting trace data. This provides comprehensive observability to identify exactly where performance issues or failed LLM calls occur within your applications.

How do I list recent execution traces for my LLM project?▼

To list recent execution traces for your LLM project, use the langsmith trace list command. This displays the last 10 traces from your current project to help you start debugging and monitoring performance.

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