What problem does it solve? Operating hosted Beaker optimization runs requires many CLI steps—selecting the right agent and integration, resolving remote branches and datasets, authorizing launches, polling status, pulling results, and cancelling runs—each with strict preconditions and exit-code semantics that are easy to get wrong. ## Core Features & Use Cases - Run Lifecycle Management: Launch agent optimization runs with beaker run trigger, monitor with bounded polling, pull completed results, and cancel runs safely with explicit authorization. - Launch Discovery: Verify auth and GitHub connection, select the correct agent by matching github_repository, list remote branches and hosted datasets, and check required environment variables before launching. - Model Comparison: Optionally launch comparison runs with 1–8 --optimization-model values drawn from beaker model list --available-only, only when the developer explicitly requests it. - Use Case: A developer asks to "launch a Beaker optimization run on the staging branch with dataset prompts@v3." The skill validates the connection, confirms the branch and dataset, states the exact launch parameters, and triggers the run—then reports the full run ID and UI URL. ## Quick Start Ask your agent to launch a Beaker optimization run for this repository and it will discover the connected agent, dataset, and branch before triggering the hosted run.