LangSmith Traces

Integrate LangSmith tracing into Python and TypeScript LLM applications.

Updated Feb 24, 2026

Search Tags:#typescript #python #observability #tracing #data export #langsmith #llm debugging

Ready to run

npx skills add https://github.com/Diploma-pending/test-case --skill langsmith-traces-diploma-pending

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: LangSmith Traces
Source: https://github.com/Diploma-pending/test-case/tree/main/.agents/skills/langsmith-traces
Command: npx skills add https://github.com/Diploma-pending/test-case --skill langsmith-traces-diploma-pending

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langsmith, click, rich, python-dotenv, commander, chalk, cli-table3, ora, dotenv, tsx, typescript, @types/node, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you understand and manage the execution of your LLM applications by providing tools to trace, query, and export execution data.

Core Features & Use Cases

Add Tracing: Integrate LangSmith tracing into your Python or TypeScript applications, whether using frameworks like LangChain or custom code.
Query Traces: Retrieve, filter, and analyze trace data to debug issues, understand performance, and generate datasets.
Export Data: Export trace and run data in JSONL format for further analysis or dataset creation.
Use Case: Debug a complex RAG pipeline by examining the individual LLM calls, retrieved documents, and prompt/output for each step within a specific trace.

Quick Start

Use the langsmith-traces skill to list the last 10 traces from your project.

Frequently Asked Questions about LangSmith Traces

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

FAQPage Schema

How do I add LangSmith tracing to my Python or TypeScript LLM application?▼

Add LangSmith tracing by integrating the provided scripts into your Python or TypeScript environment. This supports both framework-based integrations like LangChain and custom LLM code to capture execution data.

What is the best way to debug a complex RAG pipeline using LLM traces?▼

Debug a RAG pipeline by querying LangSmith traces to examine individual LLM calls, retrieved documents, and prompt outputs. This isolates specific steps within a trace to identify performance issues or errors.

Can I export LangSmith trace data to JSONL for dataset creation?▼

Export LangSmith trace and run data in JSONL format using the provided scripts. This enables further offline analysis and dataset creation with various filtering and metadata options.

How do I list and filter recent LLM traces from my project?▼

List recent LLM traces by running the provided scripts to retrieve the last executions from your project. You can apply various filtering and metadata options to narrow down the trace data.

Does LangSmith tracing work with custom LLM code or only with frameworks like LangChain?▼

LangSmith tracing works with both framework-based integrations like LangChain and custom LLM code. The provided tools support Python and TypeScript environments for flexible execution data capture.

What dependencies do I need to query LangSmith traces in a TypeScript environment?▼

Querying traces in a TypeScript environment requires dependencies like commander, chalk, cli-table3, ora, dotenv, and tsx. Python environments use langsmith, click, rich, and python-dotenv.