are-implement

You can benchmark AI code implementations by orchestrating side-by-side dual-branch runs that compare results with and without ARE docs, collecting metrics like files touched, tests run, and quality scores.

Yes, you can compare code changes across git worktrees by running side-by-side AI implementations that target code-change tasks across branches and worktrees to measure the impact of ARE documentation.

Evaluating automated planning and implementation collects metrics such as files touched, tests run, build results, latency, and quality evaluations to quantify the impact of documentation.

Yes, the dual-branch implementation comparison supports optional plan reuse and branching, allowing you to orchestrate side-by-side AI runs while enforcing safe execution and evaluation flags.

You generate a concise results report by triggering the implementation comparison task, which executes both environments, collects evaluation metrics, and returns the findings.