What problem does it solve? When a pull request triggers an Argos visual regression build with detected changes, someone must decide whether each screenshot diff is intentional, a regression, or a flaky capture before approving. This Skill turns that manual screenshot-by-screenshot judgment into a structured, evidence-based review workflow. ## Core Features & Use Cases - Build status triage: Inspects the Argos build via the argos CLI and routes by status (changes-detected, pending, rejected, orphan) before doing any review work. - Flakiness analysis: Weighs test history metrics (flakiness, stability, occurrences) against capture-level signals (spinners, retries, mid-animation states) to distinguish real regressions from noise. - Anchored review output: Posts per-diff comments pinned to regions, submits approve/reject reviews, and can silence confirmed recurring flakes with change ignore. - Use Case: A PR shows an Argos status check with 12 changed snapshots. The Skill fetches the diffs, identifies 10 as intentional style updates, flags 1 clipped button as a regression with an anchored comment, and marks 1 recurring loader flake as ignorable, then submits the review. ## Quick Start Review the Argos build linked in this pull request and tell me whether the visual diffs match the intended changes.