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analyze-website分析网站

Agent Skill

analyze-website 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

324

周安装

13

GitHub Stars

4

下载量

105
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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:analyze-website(分析网站)
来源仓库:https://github.com/klamping/webdriverio-skills
仓库路径:skills/analyze-website
安装命令:
npx skills add https://github.com/klamping/webdriverio-skills --skill analyze-website
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/klamping/webdriverio-skills --skill analyze-website

简介

analyze-website 生成网站结构与功能地图,支持测试规划、变更影响评估与组件重要性排序。

  • 适合前端项目前期调研或回归测试设计,优先轻量扫描 HTML 与路由标签。
  • 缓存机制避免重复深搜,仅在目标未变更时复用已有分析结果。
  • 依赖 WebDriverIO 浏览器驱动,需启动本地或远程浏览器实例方可执行完整探测。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Analyze Website

Investigate and document site structure and functionality for humans and agents.

This skill produces reusable analysis artifacts that support test planning, coverage decisions, and change impact reviews.

Performance Goals

  • Minimize repeated deep scans when analysis already exists.
  • Use the lightest evidence path first (HTML/routes/labels), then deepen only as needed.
  • Reuse cached analysis for unchanged targets.

When to Use

  • You need a structured map of a website before writing or triaging tests.
  • You need component inventory and functionality importance levels.
  • You need to compare two site versions (or two snapshots) for differences.

When Not to Use

  • You only need to implement a specific test immediately.
  • You only need to run a known test file.
  • You have no page evidence (URL, HTML, screenshot, or metadata).

Inputs

Preferred inputs (use what is available):

  • URL(s) to analyze
  • screenshot(s)
  • HTML source and metadata
  • optional baseline + current versions for comparison
  • optional product context (critical flows, business priorities)

For authenticated areas, accept one of these:

  • test credentials (username/password)
  • HTML snapshots for authenticated pages
  • permission to run temporary WDIO login navigation using existing page objects

Never persist credentials in output artifacts.

Fast-Path Workflow

Use this sequence to improve speed and reduce token usage:

  1. Check for existing analysis in references/website-analysis/<target>/.
  2. If recent and target unchanged, reuse and update only affected sections.
  3. Fetch lightweight evidence first (route shell, key labels, structural markers).
  4. Only run deeper extraction (bundle/string/component scan) when lightweight evidence is insufficient.
  5. Skip version diff steps unless baseline/current inputs are explicitly provided.

For JS-heavy sites, treat static HTML as shell-only and extract structure from available bundled assets or provided screenshots.

Auth-Gated Discovery

When key functionality is behind authentication:

  1. Prefer provided authenticated HTML/snapshots for target pages.
  2. If unavailable and credentials are provided, use temporary WDIO navigation with existing login page objects.
  3. Capture only resulting page structure and feature evidence (not secret values).
  4. Mark inaccessible areas explicitly as unknown instead of guessing.

Temporary WDIO scripts should be minimal and disposable, used only to unlock page evidence for analysis.

Just-Enough Information Policy

Do not recreate the full site in exhaustive prose.

Capture only what is required to plan tests and triage/fix failures:

  • critical routes/pages
  • high-impact components and actions
  • core state transitions
  • important dependencies and risk points
  • known unknowns/gaps

Keep low-value cosmetic detail brief unless it affects behavior or selectors.

Analysis Model (Two-Level Structure)

Use a two-level hierarchy inspired by page-structure decomposition:

  1. Section boundaries: top-level page regions and thematic breaks
  2. Content sequences within each section: ordered subflows/components in each section

This avoids mixing page-level and component-level findings.

Investigation Workflow

  1. Validate evidence availability (URL/screenshot/HTML/version refs).
  2. Identify top-level sections (header, hero, content groups, footer, etc.).
  3. For each section, identify ordered content sequences.
  4. Build component inventory (tabs, menus, forms, tables, actions, modals, filters, pagination).
  5. Capture key functionality and interaction states.
  6. Assign importance levels to functionality.
  7. If baseline/current versions are provided, run structured diff comparison.
  8. Save outputs for downstream human/agent use.

Component Inventory Requirements

For each component/functionality, capture:

  • location (section + sequence)
  • user purpose
  • key actions/events
  • critical states (default/loading/empty/error/success)
  • dependencies (auth, API, feature flags, permissions)

Importance Scoring

Assign each functionality an importance level:

  • high: business-critical flows (auth, checkout, account access, data submission)
  • medium: primary usability and navigation flows
  • low: non-critical enhancements and cosmetic interactions

Use this weighted lens when helpful:

importance = business impact x usage frequency x change risk x failure severity

Version Comparison (When Available)

Compare baseline vs current for:

  • structural changes (sections, sequences, routes)
  • component changes (added/removed/modified)
  • interaction/state changes
  • selector/DOM changes likely to impact tests
  • visible UX and accessibility shifts

Classify diffs by impact:

  • breaking: likely to break existing tests or critical behavior
  • significant: meaningful behavior or structure change
  • minor: low-risk cosmetic or copy changes

Output Files

Write/update:

  • references/website-analysis/<target>/website-analysis.md
  • references/website-analysis/<target>/website-analysis.json
  • references/website-analysis/<target>/website-diff.md (only when comparison input exists)

Target Resolution Rule

Resolve <target> consistently:

  • Use the lowercase site host (e.g. https://demo.learnwebdriverio.com/... -> demo.learnwebdriverio.com).
  • If host is unavailable but route/page path is known, use unknown-target and record the assumed source in analysis notes.
  • For multi-site projects, keep one folder per host.
  • Do not include protocol, query params, or trailing slash in <target>.

Optional mirror for cross-skill runtime consumption:

  • .webdriverio-skills/website-analysis.md
  • .webdriverio-skills/website-analysis.json

Output Size Guidance

Use compact outputs by default:

  • website-analysis.md: concise, high-signal sections only
  • website-analysis.json: structured fields needed for downstream automation
  • include an explicit unknowns list when evidence is incomplete

Output Format (Markdown)

website-analysis.md should include:

  1. Overview and input evidence
  2. Section map (Level 1)
  3. Content sequences per section (Level 2)
  4. Component inventory
  5. Functionality importance matrix
  6. Testing implications (high-priority coverage targets)

website-diff.md should include:

  1. Baseline vs current summary
  2. Structured diff list by impact (breaking/significant/minor)
  3. Recommended test updates

Minimal JSON Shape

{
  "updatedAt": "ISO-8601",
  "sections": [],
  "sequences": [],
  "components": [],
  "functionalities": [],
  "importance": [],
  "diff": []
}

Common Mistakes

  • Skipping section-level analysis and jumping straight to components.
  • Capturing components without interaction states.
  • Assigning importance without business context.
  • Comparing versions without classifying impact.
  • Producing narrative notes without reusable structure.
  • Re-running full deep analysis when cached references are still valid.

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

33.75%
按下载量换算35

Claude

29.67%
按下载量换算31

Cursor

19.31%
按下载量换算20

Gemini CLI

9.6%
按下载量换算10

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/klamping/webdriverio-skills --skill analyze-website 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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

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