Review Before Generation: The Better Foundation for Building AI Code Skills

AI coding tools consistently produce quality issues—inconsistent naming, poor error handling, misaligned test strategies—but defining comprehensive quality standards upfront is unrealistic. Rather than writing perfect generation prompts from scratch, the review-first approach starts by building skills that catch problems incrementally, then extracts these criteria for reuse in generation skills. This strategy is more measurable, incremental, and practical than attempting to anticipate all quality dimensions before building.