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Agent Skill · 研究检索

web-accessibility(网络可访问性)

用于辅助无障碍访问检查、页面可用性审计和前端可访问性改进。它适合让 Agent 检查语义标签、键盘操作、颜色对比、ARIA 属性和自动化检测结果。使用时需要结合真实页面和浏览器验证,不应只依赖静态文本判断;涉及修复建议时,应兼顾设计系统、组件复用和 WCAG 等通用无障碍规范。

web-accessibility 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 35,283。

总安装 2,112周安装 88GitHub Stars 11下载 704核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:web-accessibility(网络可访问性)
来源仓库:https://github.com/akillness/oh-my-skills
仓库路径:skills/web-accessibility
安装命令:
npx skills add https://github.com/akillness/oh-my-skills --skill web-accessibility
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/akillness/oh-my-skills --skill web-accessibility

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于识别和修复网页可访问性问题,聚焦语义标签、键盘操作和 ARIA 属性缺陷。适合自动化检测与人工验证结合的审计场景,区分机器可发现和可读性问题。使用时需配合真实页面和浏览器测试,避免仅依赖静态文本分析结果。

安装命令:npx skills add https://github.com/akillness/oh-my-skills --skill web-accessibility 修复建议应遵循 WCAG 规范,同时考虑设计系统和组件复用性,不破坏现有交互逻辑。

来源仓库内路径:skills/web-accessibility

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/akillness/oh-my-skills --skill web-accessibili…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

web-accessibility 怎么安装?

在终端执行 npx skills add https://github.com/akillness/oh-my-skills --skill web-accessibility。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

web-accessibility 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

web-accessibility 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

web-accessibility 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

web-accessibility 用的人多吗?

公开数据是累计安装 2,112 次,近一周安装 88 次,下载 704 次,GitHub 11 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

web-accessibility 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
web-accessibility

网络可访问性 · 本页

2,11211操作浏览器未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Web Accessibility

Use this skill when the job is to name the failing accessibility surface, fix it at the right layer, and leave behind a short remediation + verification packet.

The job is not to dump generic WCAG prose, paste raw scanner output, or absorb every neighboring frontend concern.

This skill should:

  1. classify the failing accessibility surface,
  2. separate automated findings from manual or assistive-technology follow-up,
  3. choose the smallest credible remediation packet,
  4. keep routed-app feedback and focus behavior explicit,
  5. route broader design/layout/component-governance work honestly.

Read these support docs first:

When to use this skill

  • A team says “make this accessible” and the missing accessibility surface is still unclear
  • axe, Lighthouse, Accessibility Insights, Pa11y, QA notes, or user reports need to be turned into one remediation plan instead of a raw finding dump
  • You need to decide whether the main issue is semantics, keyboard/focus, labels/announcements, reflow/contrast/motion, media alternatives, or routed-app navigation feedback
  • A modal, form, nav, menu, table, dashboard, or routed flow needs manual-vs-automated verification guidance before release
  • Screen-reader, keyboard-only, or zoom/reflow issues are suspected, but ownership and next checks are unclear

When not to use this skill

  • The main task is broad UI polish, heuristic review, hierarchy, or interface consistency → web-design-guidelines
  • The main task is reusable primitive / slot / variant API design or component-family ownership → ui-component-patterns
  • The main task is viewport adaptation, breakpoint strategy, container-query planning, or layout overflow control → responsive-design
  • The main task is token governance, contribution rules, or system-wide frontend standards → design-system
  • The task is only to run one tool and paste raw results; run the tool directly, then return here to prioritize remediation and manual follow-up

Instructions

Step 1: Frame the accessibility job before naming fixes

Capture the minimum packet first.

accessibility_intake:
  surface: page | routed-flow | modal | form | nav | menu | table | dashboard | component-family | mixed | unknown
  workflow_type: audit-review | remediation-pass | release-readiness | regression-follow-up | user-reported-bug | design-system-follow-up
  signal_source: axe | lighthouse | accessibility-insights | pa11y | manual-qa | screen-reader-report | user-feedback | mixed | unknown
  primary_surface: semantics | keyboard-focus | labels-announcements | visual-perception-reflow | media-alternatives | routed-navigation-feedback | mixed | unknown
  severity: blocker | major | medium | low | unknown
  ownership: app-team | frontend-platform | design-system | qa-accessibility | shared | unknown

Rule: do not start with “add ARIA,” “run axe again,” or “quote WCAG 2.1.” First label the failing accessibility surface.

Step 2: Choose exactly one primary remediation packet

Use the router in references/intake-packets-and-route-outs.md.

Primary packets:

  1. semantics-structure
  2. keyboard-focus
  3. labels-announcements
  4. visual-perception-reflow
  5. media-alternatives
  6. routed-navigation-feedback

Pick the highest-risk user-facing failure as primary. List everything else as follow-up, not as equal co-owners.

Step 3: Keep the invariants visible

These rules survive every answer:

  • automated tools accelerate discovery, but they do not prove accessibility completeness
  • native HTML semantics beat ARIA patching when native controls already solve the problem
  • keyboard/focus failures in interactive flows usually outrank cosmetic cleanups
  • routed apps need explicit focus and announcement decisions because browser navigation cues disappear
  • labels, instructions, errors, and async status text are part of task completion, not polish
  • every remediation recommendation needs a matching manual verification step

Step 4: Build the accessibility remediation packet

Return this structure:

# Accessibility Remediation Packet

## Scope
- Surface:
- Workflow type:
- Primary packet:
- Confidence: high | medium | low

## Current signal
- Tool or report source:
- What is already known:
- What still needs direct verification:

## Highest-risk gaps
1. ...
2. ...
3. ...

## Recommended first slice
1. ...
2. ...
3. ...

## Verification plan
- Automated re-check:
- Manual keyboard / focus:
- Manual screen-reader / AT:
- Visual / zoom / motion / reflow:

## Ownership and route-outs
- Primary owner:
- Adjacent skills / teams:

Step 5: Use the packet, not a giant checklist

Pull the packet from references/intake-packets-and-route-outs.md.

Packet rules:

  • semantics-structure → landmarks, headings, lists, tables, buttons/links, form markup, native-first fixes
  • keyboard-focus → tab order, visible focus, trap/escape behavior, initial focus, focus return, composite widget behavior
  • labels-announcements → accessible names, helper/error relationships, live regions, status/error messaging, required-state clarity
  • visual-perception-reflow → contrast, reduced motion, zoom, reflow, target visibility, state visibility
  • media-alternatives → alt text, decorative-vs-informative imagery, captions, transcripts, fallback descriptions
  • routed-navigation-feedback → page title / heading announcement, route-change focus strategy, SPA/app-router cues, async load state announcements

Step 6: Separate automated findings from manual proof

Use this split in every serious answer:

  • Automated-friendly — missing labels, duplicate IDs, invalid ARIA, simple contrast failures, landmark/heading gaps
  • Manual keyboard/focus — tab sequence, visible focus, trap behavior, initial focus, focus return, menu/listbox/dialog interaction
  • Manual AT / content quality — announcement usefulness, alt-text quality, label clarity, route-change comprehension, async feedback quality

If the request starts from a scanner, say explicitly that the scanner is the input artifact, not the finished answer.

Step 7: Route adjacent work explicitly

Use these route-outs when the problem crosses boundaries:

If the real job is...Route to...
broad UI/design review, hierarchy, polish, or guideline complianceweb-design-guidelines
reusable component API / primitive ownership / slot-variant designui-component-patterns
viewport/container layout strategy or breakpoint planningresponsive-design
token governance or system-wide frontend standardsdesign-system
React/Next performance or hydration behaviorreact-best-practices

Output expectations

A strong answer from this skill should:

  1. identify the primary failing accessibility surface,
  2. recommend one bounded remediation packet,
  3. name the manual verification still required,
  4. avoid equating a scanner pass with completion,
  5. route broader frontend ownership questions outward instead of absorbing them.

Examples

Example 1: modal audit after axe

Input

Audit this checkout modal for accessibility issues and tell me what to test manually after axe.

Output direction

  • choose keyboard-focus or labels-announcements
  • treat axe as the input artifact, not the whole workflow
  • verify initial focus, trap behavior, focus return, and announcement quality
  • keep broader visual-polish critique out unless it materially affects accessibility

Example 2: routed app navigation confusion

Input

Screen-reader users say our React app changes routes but the new page is not announced and focus stays on the old nav link.

Output direction

  • choose routed-navigation-feedback
  • classify title/heading announcement plus focus-reset strategy
  • include manual AT verification after the fix
  • avoid turning the task into generic routing architecture work

Example 3: component-boundary confusion

Input

Our button primitive API is messy and some variants are not accessible. Is this web-accessibility or ui-component-patterns?

Output direction

  • keep accessible-name, focus-state, and disabled/loading announcement fixes in web-accessibility
  • route primitive API / variant ownership to ui-component-patterns
  • split the plan instead of forcing one skill to own everything

Example 4: manual checks after Lighthouse

Input

Lighthouse says contrast is okay now. What should I still test manually?

Output direction

  • treat this as verification planning, not score celebration
  • verify keyboard order, focus visibility, routed-flow cues, and screen-reader announcement quality where relevant
  • include zoom/reflow and reduced-motion checks when the interface depends on them

Best practices

  1. Start with the user task and failing surface, not the rule number.
  2. Treat automated tools as accelerators, not as proof of accessibility completeness.
  3. Prefer native HTML semantics before ARIA-heavy patches.
  4. Keep focus behavior intentional for overlays, route changes, and async validation.
  5. Separate remediation packets from broader design-review or component-architecture work.
  6. When unsure, name the manual verification still required instead of pretending the scan is enough.

References

平台分布

Codex

38.19%
按下载量换算269

Claude

27.82%
按下载量换算196

Cursor

19.36%
按下载量换算136

Gemini CLI

9.38%
按下载量换算66

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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