langchain-ai/langsmith-skills.
4 skills★ 164View on GitHub ↗
- 100/100
langsmith-custom-apps
INVOKE THIS SKILL when building, iterating on, copying, or sharing a LangSmith Custom App — a React/TypeScript UI that runs inside LangSmith and reads the LangSmith API. Covers the langsmith apps CLI, pulling an existing app's source, replicating an app into another workspace, verifying app logic without a browser, and sanitizing an app before sending it outside your org. Uses the langsmith CLI tool.
- 100/100
langsmith-dataset
INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
- 100/100
langsmith-evaluator
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses the langsmith CLI tool.
- 100/100
langsmith-online-eval-engineering
Design, test, create, and attach LangSmith online evaluators for production traces or conversation threads. Use for workspace evaluators, run or thread rules, sampling, filters, backfills, and evaluator monitoring; use eval-engineering for Harbor tasks and agent benchmarks.