meta-verify

You can verify AI output by running an independent quality check that evaluates the generated content against originating operational rules and quality gate criteria. This second-pass validation ensures accuracy and adherence before execution.

An independent quality gate evaluation is a context-agnostic validation process that assesses AI-generated output against predefined operational guidelines and quality standards, ensuring unbiased accuracy without relying on the original generating context.

Yes, you can apply this independent validation to pre-mortem reports, positioning briefs, and other AI-generated outputs. It checks the content against the originating skill's operational rules before you act on the results.

You can perform a quality check on a pre-mortem report by executing the verify command with the pre-mortem argument. This triggers an independent evaluation against the originating operational rules and quality gate criteria.

No, the AI output validation is context-agnostic. It ensures the evaluation remains completely unbiased and does not rely on the company context or environment that originally generated the output.

You should use an independent evaluation whenever you need to act on AI-generated output and must ensure it meets strict quality standards. It serves as a pre-execution validation step to catch inaccuracies before implementation.