Trace, evaluate, and manage prompts for LLM applications via LangSmith SDKs.
npx skills add https://github.com/akillness/oh-my-skills --skill langsmith-akillness
Please help me install this Agent Skill. Skill: langsmith Source: https://github.com/akillness/oh-my-skills/tree/main/.agent-skills/langsmith Command: npx skills add https://github.com/akillness/oh-my-skills --skill langsmith-akillness
LangSmith provides end-to-end observability, tracing, evaluation, and prompt management for LLM applications and AI agents, helping teams debug, monitor, and optimize their pipelines.
Install the LangSmith SDKs for Python or TypeScript and run the quickstart examples to enable tracing and evaluation.
High-intent search queries and answers about installing and using this skill.
To enable tracing for LLM applications, you must set the LANGSMITH_TRACING environment variable and use the LangSmith SDKs. This provides end-to-end observability for monitoring LLM calls, tools, and retrievers.
Evaluating LLM pipelines is best handled through dataset versioning and benchmarking. You can run offline and online evaluations using human or automated feedback workflows to test for regressions in your LLM applications.
Yes, LangSmith observability supports TypeScript environments and includes specific wrappers for OpenAI. It requires the LangSmith SDKs for Python or TypeScript to integrate tracing and evaluation into your LLM pipelines.
Yes, you can manage prompts for LLM agents using the Prompt Hub. It provides dataset-driven benchmarking and prompt management capabilities to help debug, monitor, and optimize your LLM application pipelines.
Openevals is an optional dependency required specifically for advanced evaluation of LLM tracing. Without it, you still get core observability, but advanced automated feedback workflows for LLM applications will be limited.
Harmeet10000Instrument and query LangSmith traces in Python and TypeScript projects.
trueraInstrument LLM apps to capture traces for evaluation and debugging.
eco2-teamTrack LLM calls, token usage, and costs in LangChain/LangGraph applications.
IgorGanapolskyMonitor LangSmith traces, runs, and performance metrics via Python API.
