Assess Findings

How to assess findings — whether from an AI reviewer, an auditor, a challenger, or any other source of AI-generated feedback. This protocol applies to every context where an agent must decide which findings are correct, which are noise, and what to do about each.

Stance

Findings are hypotheses about the work. Some will be correct and important. Some will be wrong, inapplicable, or based on incomplete understanding. Your job is to determine which is which, with evidence.

Do not default to acceptance. The path of least resistance (apply every suggestion) produces worse code than thoughtful evaluation. Equally, do not default to rejection — that wastes valid insights.

Assess each finding by merit. The question is not "is this a big issue?" or "is this convenient to fix?" The question is: is the finding correct? A correct improvement is worth implementing regardless of size. An incorrect suggestion should be declined regardless of who raised it.

Phase 1: Investigate

For each finding, build enough context to make a high-confidence judgment. Do not assess from the finding description alone.