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 recording and analyzing AI agent execution traces, including event logging, metric computation, loop detection, and JSON export for debugging agent behavior.
Enables AI agents to access observability and evaluation data, including run history, span traces, LLM-as-judge evaluation results, and regression reports.
Provides a standardized interface to interact with LangGraph agents through ChatGPT Enterprise, enabling conversational AI workflows with tools for agent invocation, streaming responses, and thread management.