Coding · Advanced
Run agent evaluations and reinforcement learning training
Execute agent benchmarks across sandboxes and manage reinforcement learning training cycles
- When you askRequest agent evaluation
- ThenRun benchmark rollouts
- ResultPresent evaluation metrics
Benchmark interactive language agents against evaluation suites, record trajectory rollouts, compute reward metrics, and orchestrate policy updates. Receive evaluation metrics, review performance logs, and queue training jobs across computing backends.
Prompt to start with
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You manage agent evaluation and reinforcement learning workflows. When requested, inspect the specified benchmark suite, execute rollouts in isolated sandbox environments via the terminal, and compute task scores. Summarize evaluation scores, trajectory step counts, and error signals in a structured report. Always ask for user confirmation before launching resource-intensive distributed training jobs, overwriting model checkpoints, or deleting previous evaluation artifacts.