langsmith-dataset

Create, manage, and upload evaluation datasets to LangSmith via CLI and SDK.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1 --skill langsmith-dataset-hyunjunjeon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langsmith-dataset
Source: https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1/tree/main/Day-01/.agents/skills/langsmith-dataset
Command: npx skills add https://github.com/HyunjunJeon/SDS-AX-Advanced-2026-1 --skill langsmith-dataset-hyunjunjeon

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

LangSmith dataset management and upload workflows can be time-consuming and error-prone; this skill automates the creation, organization, and ingestion of evaluation datasets for testing and validation.

Core Features & Use Cases

  • Create, manage, and upload evaluation datasets to LangSmith for testing and validation.
  • Support common dataset types: final_response, single_step, trajectory, and RAG, with CLI and SDK workflows.
  • Guidance for exporting traces, converting them into LangSmith-compatible datasets, and running end-to-end validation experiments.

Quick Start

Create a new LangSmith dataset and upload it to your project using the CLI.

Frequently Asked Questions about langsmith-dataset

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

FAQPage Schema
How do I upload evaluation datasets to LangSmith for testing?▼

You can upload evaluation datasets to LangSmith by using CLI or SDK workflows to create a dataset, add examples, and ingest them directly into your project for validation and testing.

What LangSmith dataset types are supported for evaluation?▼

LangSmith evaluation supports four main dataset types: final_response, single_step, trajectory, and RAG, each tailored for different testing and validation workflows.

Can I export LangSmith traces and convert them into evaluation datasets?▼

Yes, you can export traces from LangSmith and convert them into compatible datasets, allowing you to reuse real interaction data for end-to-end validation experiments.

Do I need to use the CLI or SDK to manage LangSmith datasets?▼

You can use either the CLI or SDK to manage LangSmith datasets; both interfaces support environment setup, dataset creation, example management, and end-to-end upload workflows.

What is the best way to automate LangSmith dataset creation and management?▼

Automating LangSmith dataset management involves using CLI or SDK scripts to programmatically create datasets, apply dataset types like RAG or trajectory, and upload examples for validation.