langsmith-dataset

Name: langsmith-dataset
Availability: InStock
Author: jxtngx

Convert LangSmith trace logs into structured JSON evaluation datasets.

2|Updated Apr 3, 2026

Search Tags:#testing #llm #evaluation #traces #datasets #langsmith

Ready to run

npx skills add https://github.com/jxtngx/dgx-lab --skill langsmith-dataset-jxtngx

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: langsmith-dataset
Source: https://github.com/jxtngx/dgx-lab/tree/main/.cursor/skills/langsmith-dataset
Command: npx skills add https://github.com/jxtngx/dgx-lab --skill langsmith-dataset-jxtngx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langsmith.

What problem does it solve?

This skill streamlines the transition from raw trace data to structured evaluation datasets, removing the manual overhead of formatting and uploading examples for LLM testing.

Core Features & Use Cases

Trace-to-Dataset Pipeline: Automatically convert exported LangSmith traces into valid JSON datasets for evaluation.
CLI Management: Perform CRUD operations on datasets, examples, and experiments directly from your terminal.
Use Case: After running a series of agent experiments, use this skill to extract the most successful trajectories and upload them as a new evaluation dataset to ensure future model iterations maintain performance.

Quick Start

Use the langsmith-dataset skill to export traces from the current project and upload them as a new evaluation dataset named Evaluation Set Alpha.

Frequently Asked Questions about langsmith-dataset

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

FAQPage Schema

How do I convert LangSmith traces into evaluation datasets?▼

You can convert LangSmith traces into evaluation datasets by transforming exported trace logs into structured JSON examples. This process formats raw agent trajectories into valid datasets for testing LLM behavior.

What is the best way to manage LLM evaluation datasets from the terminal?▼

Managing LLM evaluation datasets from the terminal is done through the langsmith CLI. You can perform CRUD operations on datasets, examples, and experiments directly without leaving your command line environment.

Do I need the langsmith SDK to upload test datasets?▼

Yes, you need both the langsmith CLI and SDK to upload test datasets. These dependencies interface with the LangSmith API to handle dataset versioning and experiment tracking.

Can I use successful agent trajectories as new evaluation datasets for RAG testing?▼

Yes, you can extract successful agent trajectories and upload them as new evaluation datasets. This ensures future model iterations maintain RAG performance by testing against validated examples.

Why format raw trace logs into JSON examples for LangSmith?▼

Formatting raw trace logs into JSON examples for LangSmith removes the manual overhead of data preparation. It structures agent behavior data into a standardized format required for accurate experiment tracking and evaluation.