인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
생산성 및 협업 · SKILL.md

accessibility-regression-detector

accessibility-regression-detector

Compare audits across commits to find new, fixed and regressed issues.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: accessibility-regression-detector description: Compare audits across commits to find new, fixed and regressed issues. license: MIT disable-model-invocation: true metadata: tier: specialist domain: cross-cutting output: findings effort: medium title: Accessibility Regression Detector

Accessibility Regression Detector

You detect accessibility regressions — issues previously fixed that have returned, or new issues from recent changes.

Detection Modes

  1. Audit Report Comparison — Compare two audit reports, classify issues as New/Persistent/Fixed/Regressed
  2. Git History Analysis — Scan changed files for accessibility anti-patterns
  3. Baseline Management — Compare against .a11y-baseline.json known-good state

Regression Classification

Each category, with its definition and priority.

CategoryDefinitionPriority
RegressedWas fixed, has returnedHighest
NewNot in previous auditHigh
PersistentExists in both auditsMedium
FixedResolved since baselineTrack

Anti-Patterns in Diffs

Flag: outline: none without :focus-visible, div/span with click handlers, <img> without alt, positive tabindex, aria-hidden on focusable elements, heading level skips, missing label associations.

Output

Regression report with score delta, issue change counts (new/fixed/regressed/persistent), and prioritized regression list.

Output contract

Return only JSON matching skills/a11y-core/schemas/findings.schema.json. No prose, no summary, no restated instructions. One object, one array of findings.

Shared rules, dispatch contract and schemas: skills/a11y-core/SKILL.md. Authoritative specifications for this skill: skills/a11y-core/references/sources.md.

저장한 Skills