Inspects and manages LangSmith traces, datasets, and prompts using a context-efficient CLI optimized for Claude Code.
The LangSmith CLI skill provides a lightweight, on-demand alternative to heavy MCP servers for developers using LangSmith. It enables seamless debugging of AI chains, management of evaluation datasets, and detailed token cost analysis directly within Claude. By implementing a cache-first architecture, the skill ensures high-performance searching and offline analysis of runs, while advanced filtering capabilities—including regex and FQL—allow for surgical data extraction. This skill is essential for developers who need to monitor production LLM applications, compare experiment results, and maintain high-quality prompt repositories without leaving their terminal workflow.
Key Features
01Advanced filtering using FQL and client-side regex search across inputs and outputs.
02Efficient debugging of AI traces and run history with JSON-first output.
03Local cache-first workflow for instant searching and reduced API latency.
04Comprehensive management of LangSmith datasets, prompts, and feedback.
058 GitHub stars
06Detailed token usage and cost analysis broken down by model and provider.
Use Cases
01Debugging failed LLM traces and inspecting nested chain outputs in real-time.
02Analyzing production token costs and identifying expensive model usage patterns.
03Managing evaluation datasets and pulling prompt templates for model testing.
