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...Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context.

...The CLI is designed as a verification layer for agentic coding workflows, so an AI agent can create tests, run them, inspect failures, fix code, and rerun checks. It returns structured failure bundles that can include failing steps, screenshots, DOM snapshots, test source, root-cause hypotheses, and recommended fix targets. It supports scripting, deterministic output, JSON results, predictable exit codes, and dry-run behavior for automation. Overall, it helps teams turn AI-generated code into a more testable, repeatable, and evidence-backed development loop.