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testland/visual-baseline-gate

Consumes pre-classified visual-diff JSON and a reviewer-signed acceptance log to produce a single go/no-go CI verdict for visual regression. Blocks when intentional baseline changes lack a non-author reviewer sign-off or when regressions are present, and emits a markdown + JSON artifact for the CI step. Use this skill when the gate's input is pre-classified diff data and the enforcement concern is reviewer approval, not when the goal is fanning out to multiple engines (use a multi-engine CI orchestrator for that).

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name:
visual-baseline-gate
description:
Consumes pre-classified visual-diff JSON and a reviewer-signed acceptance log to produce a single go/no-go CI verdict for visual regression. Blocks when intentional baseline changes lack a non-author reviewer sign-off or when regressions are present, and emits a markdown + JSON artifact for the CI step. Use this skill when the gate's input is pre-classified diff data and the enforcement concern is reviewer approval, not when the goal is fanning out to multiple engines (use a multi-engine CI orchestrator for that).

visual-baseline-gate

Overview

A typical visual-regression CI run produces an engine-specific verdict (Chromatic exit code, Percy build status, Playwright snapshot pass/fail). That's not enough for a strict gate, because:

  1. Each engine treats "visual changes" differently - Chromatic exits 1 on changes (review needed), Percy returns success but flags the build pending, Playwright fails the test outright.
  2. "The author updated baselines and committed them" is not the same as "a reviewer approved the baseline change." A --update-snapshots commit is a self-approval; for safety-relevant components it should require a sign-off.

This skill defines a build-an-X workflow that consumes both the diff classifier output and an explicit acceptance log to emit a single go/no-go verdict.

When to use

  • The team uses two or more visual engines and wants one CI gate (similar in motivation to data-quality-gate in the qa-data-quality plugin, for data quality).
  • The team wants to enforce a "reviewer approval" rule on baseline updates - i.e. a --update-snapshots commit by the PR author cannot self-approve a baseline change to a critical component.
  • The team wants the classified visual-diff output to become CI-blocking rather than advisory.

If the project uses one engine only and trusts engine-native review (e.g. all changes go through Chromatic UI approval), prefer the engine's native CI integration - see the matching engine's "CI integration" section in its SKILL.md.

How to use

  1. Collect the two inputs - the pre-classified diff JSON (one record per snapshot, category in intentional | incidental | regression) and the reviewer-committed .visual-acceptance.yml (see Inputs).
  2. Run the gate decision rule - regression blocks always; intentional blocks until listed in the acceptance log; incidental warns only (see The gate decision rule).
  3. Enforce author-cannot-self-approve - verify the commit that added .visual-acceptance.yml was authored by someone other than the PR author (see Author cannot self-approve).
  4. Emit the artifact and exit - write the markdown + JSON summary and exit non-zero on a no-go verdict so CI halts. The full artifact template, the runnable CI entrypoint, and the GitHub Actions wiring are in references/artifact-and-ci-wiring.md.

Inputs

The gate consumes two inputs:

  1. Classification artifact - the pre-classified diff JSON, one record per snapshot:

    {
      "snapshot": "dashboard-mobile-375",
      "engine":   "playwright",
      "category": "intentional|incidental|regression",
      "pattern":  "text-truncation|...|null",
      "paired_change": true,
      "diff_url": "playwright-report/data/dashboard-mobile-375-diff.png"
    }
  2. Acceptance log - a YAML file at .visual-acceptance.yml committed by reviewers (NOT the PR author) that explicitly accepts each intentional baseline change for the current PR:

    # .visual-acceptance.yml - committed by reviewers in the PR's review pass
    pr: 1234
    accepted_by: reviewer-handle
    accepted_at: 2026-05-04T12:00:00Z
    snapshots:
      - snapshot: dashboard-mobile-375
        reason: "Intentional CTA color change per design spec DS-456"
      - snapshot: pricing-tablet-768
        reason: "Intentional pricing tier rename"

The acceptance file lives in the PR branch; merging the PR records the acceptance in git history.

The gate decision rule

def visual_gate(classifications, acceptance_log, *,
                require_reviewer_acceptance=True):
    accepted = {s["snapshot"] for s in acceptance_log.get("snapshots", [])}
    blockers = []
    for c in classifications:
        if c["category"] == "regression":
            blockers.append((c, "regression - blocks unconditionally"))
        elif c["category"] == "intentional" and require_reviewer_acceptance:
            if c["snapshot"] not in accepted:
                blockers.append((c, "intentional - missing reviewer acceptance"))
        elif c["category"] == "incidental":
            # incidental requires investigation but does NOT block by default
            pass

    return {
        "verdict": "no-go" if blockers else "go",
        "blockers": blockers,
        "incidentals": [c for c in classifications if c["category"] == "incidental"],
        "intentional_accepted": [c for c in classifications
                                 if c["category"] == "intentional"
                                 and c["snapshot"] in accepted],
    }

Default behavior:

  • regression -> block (always).
  • intentional -> block UNTIL listed in .visual-acceptance.yml.
  • incidental -> surface as a warning, do not block.

For low-risk projects, set require_reviewer_acceptance=False so intentional changes pass without explicit acceptance - this collapses the gate to "block on regressions only."

Author cannot self-approve

For a stricter gate, validate that the commit adding .visual-acceptance.yml was authored by someone other than the PR author:

ACCEPTANCE_AUTHOR=$(git log --format='%ae' -1 .visual-acceptance.yml)
PR_AUTHOR=$(gh pr view --json author --jq '.author.login + "@..."')

if [[ "$ACCEPTANCE_AUTHOR" == "$PR_AUTHOR" ]]; then
  echo "ERROR: PR author cannot self-approve baseline changes"
  exit 1
fi

This is the visual-regression analog of GitHub's "require approval from someone other than the last committer" branch protection.

Worked example

Run the gate on one build. The classification step emitted three records, and one reviewer committed an acceptance log:

classifications = [
    {"snapshot": "dashboard-mobile-375", "engine": "playwright", "category": "regression"},
    {"snapshot": "pricing-tablet-768",   "engine": "percy",      "category": "intentional"},
    {"snapshot": "hero-desktop-1280",    "engine": "chromatic",  "category": "intentional"},
]
acceptance_log = {"snapshots": [{"snapshot": "hero-desktop-1280",
                                 "reason": "Intentional hero copy update per DS-789"}]}

result = visual_gate(classifications, acceptance_log)

Walking the rule per record:

SnapshotCategoryIn acceptance log?Outcome
dashboard-mobile-375regressionn/ablock - regressions always block
pricing-tablet-768intentionalnoblock - missing reviewer acceptance
hero-desktop-1280intentionalyespass - reviewer signed off

result["verdict"] is "no-go" (two blockers), so the CI step exits non-zero and the merge is held. The gate prints:

# Visual Baseline Gate - verdict: NO-GO
- playwright :: dashboard-mobile-375 :: regression - blocks unconditionally
- percy :: pricing-tablet-768 :: intentional - missing reviewer acceptance

To turn this build green, a non-author reviewer either fixes the dashboard-mobile-375 regression or, if the diff is actually intended, adds both snapshots to .visual-acceptance.yml and re-runs the gate. The full markdown + JSON artifact and the CI wiring that surfaces this output are in references/artifact-and-ci-wiring.md.

References

  • percy-visual-regression-testing
  • chromatic-visual-regression-testing
  • playwright-snapshots
  • storybook-visual-regression-testing
  • visual-baseline-conventions - the conventions this gate enforces.
  • data-quality-gate - sibling gate skill for data-quality results, same artifact shape.
Workspace
testland
Visibility
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