Retrieve detailed information about a specific Airflow DAG run, including its state, start and end times, duration, run type, configuration, and execution metadata.
Deploy files directly to Cloud Run by providing their contents in a chat context. Specify filenames and content for quick deployment without local file storage.
Retrieve a specific autouser run including evaluation summaries and a viewUrl deep-link to open the run with session replay directly in the Autousers app. Requires evaluationId and runId.
Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.
Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.
Run a data pipeline from a specified project directory and branch, returning a job ID and success/failure. Supports parameter templating and dry-run mode.
Upload local files to Google Cloud Run by specifying absolute file paths. Enables deployment of local filesystem assets to a specified Cloud Run service in the user's Google Cloud project.
Deploy a local folder to Google Cloud Run by specifying the folder's absolute path, project ID, and optional region and service name. Simplifies deploying entire folder contents to a Cloud Run service.
Retrieve per-turn token usage and cost telemetry for a specific autouser run. Provide evaluation ID and run ID to get detailed cost breakdown per turn.