Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.
Enables running and grading AI agent evaluations, and applying runtime guardrails that check or block unsafe tool calls through dedicated guardrail tools.
Enables recording and analyzing AI agent execution traces, including event logging, metric computation, loop detection, and JSON export for debugging agent behavior.