Conciseness

The body is efficient and assumes domain competence - engine exit-code semantics ("Chromatic ... exit code `1` = `BUILD_HAS_CHANGES`") are non-obvious and load-bearing rather than padding - but the worked example partially restates the decision rule and the Overview motivation could be tightened slightly. It sits above anchor 3 (no significant unnecessary explanation) but short of anchor 5's every-token-earns-its-place bar.

Actionability

The `visual_gate` Python function is executable and copy-paste ready, and both input formats are given as concrete schemas, but the author-cannot-self-approve bash snippet contains the placeholder `'.author.login + "@..."'` that cannot run as written - a minor gap that keeps it below the fully-executable anchor.

Workflow Clarity

The six-step emit sequence is explicit with validation checkpoints throughout: fail closed on a missing classifier run, verdict precedence (BLOCK > REVIEW > OK), escalation to BLOCK on self-approval, and a concrete error-recovery loop ("a non-author reviewer either fixes the regression or ... adds both snapshots to .visual-acceptance.yml and re-runs the gate"). This matches the anchor for clear sequencing with explicit validation and feedback loops.

Progressive Disclosure

The SKILL.md keeps the decision rule and worked example inline while consistently delegating artifact templates, the runnable CI script, and GitHub Actions wiring to the existing, verified one-level-deep reference `references/artifact-and-ci-wiring.md`, signaled with clear links at each point of need. Content is appropriately split and navigation is easy.

Specificity

The description enumerates multiple concrete actions - "blocks on regressions", "blocks ... on intended baseline changes without sign-off from a reviewer who is not the author", "fails closed when the classifier did not run", and "writes visual-gate.json and .md" - giving comprehensive, behavior-level coverage rather than vague capability claims.

Completeness

It explicitly answers both questions: "Use when visual diffs are already classified and CI needs one binding go/no-go" states the trigger concretely, and the action list states exactly what the skill does. The explicit "Use when" clause is present, and its specificity puts it above the anchor where the "when" could be more explicit.

Trigger Term Quality

Good natural keyword coverage ("visual diffs", "CI", "go/no-go", "regressions", "baseline changes", "sign-off"), but common variations a user might say - "visual regression", "snapshots", engine names like Chromatic/Percy/Playwright - are absent, matching the anchor of good coverage with a few natural terms missing rather than comprehensive synonym coverage.

Distinctiveness Conflict Risk

"visual diffs are already classified" cleanly separates this gate from the upstream classifier skill, and the reviewer-sign-off requirement carves out a clear niche with distinct triggers, so conflict risk with sibling visual-regression skills is minimal.