Token导航 LogoToken导航TokenDH.com
前端设计操作浏览器github未标认证来源可访问许可证需确认审计通过

test-macos-snapshots测试 macOS snapshots

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

303

周安装

13

GitHub Stars

5

下载量

106
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:test-macos-snapshots(测试 macOS snapshots)
来源仓库:https://github.com/yigitkonur/skills-by-yigitkonur
仓库路径:skills/test-macos-snapshots
安装命令:
npx skills add https://github.com/yigitkonur/skills-by-yigitkonur --skill test-macos-snapshots
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/yigitkonur/skills-by-yigitkonur --skill test-macos-snapshots

简介

用于辅助测试设计、自动化测试、用例整理和回归验证。

  • 适合编写单元测试、端到端测试或根据日志定位问题。
  • 需确认项目测试框架、运行命令和夹具数据后使用。test-macos-snapshots 属于前端设计类 Skill,可作为该场景下的辅助能力补充。
  • 涉及浏览器或外部服务时应区分模拟环境与生产环境。
  • 安装方式:通过 npx 从指定 GitHub 仓库添加。

SKILL.md

Test macOS Snapshots

Validate one macOS UI state at a time with an explicit expectation-first loop. Declare what the screenshot must prove before capture, then compare the image against that contract and fix the right layer.

Trigger boundary

Use this skill when you need to:

  • validate a macOS window, sheet, or screen with screenshots
  • choose or improve a deterministic snapshot automation path
  • compare expected UI state against a captured image
  • explain visual drift and decide whether the fix belongs in the app, the automation, or the expectation

Do not use this skill when:

  • the main job is designing or building the UI rather than validating it
  • the main job is driving a live browser; use run-playwright or run-agent-browser for browser control
  • the task is diagnosing runtime internals with a debugger or devtools instead of checking known UI expectations

Non-negotiable rules

  1. State the expectation before capture. Do not inspect a screenshot first and retrofit the expected state afterward.
  2. Validate one target state per run. Do not batch multiple unrelated windows or flows into one screenshot verdict.
  3. Prefer the most deterministic capture path already available. Use project-native rendering or UI tests before Accessibility or OS-level screenshots.
  4. Record layout facts that affect interpretation. Note collapsed sidebars, compact toolbars, split-view sizes, or alternate navigation chrome before you classify drift.
  5. Separate deterministic structure from data-dependent variation. Item names, timestamps, counts, and remote content may vary even when the screenshot is correct.
  6. Explain the result in three buckets. Always report Matches, Drift, and Better than expected.
  7. Fix the narrowest correct layer and rerun. Automation bugs, app bugs, and over-specific expectations are different problems.

Minimal read sets

One macOS window or sheet

Read these first:

  • references/expectation-loop.md
  • references/drift-analysis.md

Need to choose a capture path

Read these first:

  • references/capture-modes.md
  • references/expectation-loop.md

Blank, stale, clipped, or focus-dependent screenshot

Read these first:

  • references/troubleshooting.md
  • references/drift-analysis.md

Standard workflow

1. Choose the capture path

  • Inspect the project for existing screenshot or UI-test entrypoints before inventing new automation.
  • Prefer capture modes in this order: in-app or in-process rendering, built-in UI-test harness, browser driver for hybrid apps, then Accessibility or window-capture fallback.
  • Tell the user which path you chose and why it is safer than the alternatives you rejected.

Use references/capture-modes.md when the project exposes multiple possible routes.

2. Declare the expected state

Write 3-7 bullets covering:

  • target window, sheet, or screen
  • active section or navigation state through the affordance that is actually visible in the current layout
  • main visible content block or headline
  • controls, labels, or options that must be visible
  • one or two failure signatures that must not appear

Also separate:

  • deterministic structure
  • layout facts that affect interpretation
  • data-dependent variation

Use references/expectation-loop.md for the exact contract shape.

3. Capture exactly one target state

  • Run one command or one test entrypoint for the chosen state.
  • Save the absolute path to the resulting image.
  • Prefer condition-based waits or app-ready signals over blind sleeps.
  • If the capture emits multiple images, explicitly choose the file that matches the target state and say why.

4. Compare expectation against observation

Report the screenshot in three buckets:

  • Matches — visible evidence that proves the expected state is present
  • Drift — what differs from the contract and why it likely happened
  • Better than expected — extra valid evidence the image provides beyond the original contract

Use references/drift-analysis.md to classify the mismatch before you change anything.

5. Fix the right layer and rerun

  • Fix the automation when the wrong state was selected, the capture raced the UI, or the image is stale or clipped.
  • Fix the app when the screenshot exposes a real layout, state, or rendering regression.
  • Fix the expectation only when the screenshot is structurally correct and your contract was too specific.

Rerun the same target after the fix. Stop after a clean pass or after three iterations with a clear residual-risk note.

Do this, not that

Do thisNot that
Write the expected state before captureInfer expectations from the screenshot after the fact
Use project-native or test-harness capture when it existsStart with Accessibility scripting by default
Prove navigation state using the visible affordance in the current layoutRequire a sidebar highlight when the layout only shows a section title
Record actual selected item names when the content is data-dependentHardcode unstable names into the expectation
Use Matches, Drift, and Better than expectedReturn only "looks good" or "looks wrong"
Rerun the same target after the fixDeclare success on a different screenshot

Reference routing

NeedReference
Choosing between in-app, UI-test, browser, and fallback capture pathsreferences/capture-modes.md
Writing the expectation contract and running the compare loopreferences/expectation-loop.md
Classifying mismatches and picking the fix layerreferences/drift-analysis.md
Recovering from blank, stale, clipped, or focus-dependent capturesreferences/troubleshooting.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.9%
按下载量换算38

Claude

31%
按下载量换算33

Cursor

18.38%
按下载量换算19

Gemini CLI

11.11%
按下载量换算12

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills