lib/cmetrics/docs/ai/code-review.md
Find actionable defects and regression risks in a proposed change.
Use for pull requests, local diffs, dependency updates, and pre-release audits.
Run focused tests that can confirm or reject each high-confidence finding. For codec changes, inspect both encoding and decoding and relevant format conversions. Use sanitizer or benchmark evidence where the claim depends on it.
List findings by severity with file/line, failure scenario, evidence, and the smallest corrective action. Then list validation gaps and a short overall risk assessment. Do not bury findings in a general summary.
Do not request speculative changes without a concrete failure mode. Escalate public API, ABI, wire-format, or cross-repository policy decisions.