菜单
This skill should be used when the user asks about "site audit", "on-page audit", "lighthouse audit", "page speed", "technical SEO audit", "crawl site", "page analysis", "content analysis", "technology detection", or needs to analyze website pages and content using DataForSEO.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Agents-Store/claude-plugins --skill site-audit命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
This skill should be used when the user reports a problem with macstack-dev or the MACSTACK standard — "this skill did the wrong thing", "the schema is missing a field", "the passport for X is wrong", "send macstack feedback", "improve the schema based on my edit", "fix the macstack plugin" — and the fix must land in the right source (plugin, schema repo, or registry repo).
This skill should be used when the user asks to "set up Infisical for this project", "create .infisical.json", "pull the env keys", "wire the env", "sync secrets", or scaffold-project reaches the env step. Creates .infisical.json, pulls .env.prod/.env.dev, ensures every key from macstack.json resources.accesses exists, and installs the mandatory secrets scripts and commands.
This skill should be used when the user asks to "scaffold the project from macstack.json", "create the project working files", "generate project files from the spec", "build the project from macstack.json", or after a macstack.json is validated and the working tree must be built. Creates project files strictly in the prototype → stack plugins → dev plugins order.
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基于 SOC 职业分类
| name | site-audit |
| description | This skill should be used when the user asks about "site audit", "on-page audit", "lighthouse audit", "page speed", "technical SEO audit", "crawl site", "page analysis", "content analysis", "technology detection", or needs to analyze website pages and content using DataForSEO. |
Perform technical SEO audits, content analysis, technology detection, and domain intelligence using DataForSEO on-page, content analysis, and domain analytics tools.
| Tool | Description |
|---|---|
on_page_lighthouse | Run Google Lighthouse audit on a URL |
on_page_instant_pages | Get page-level optimization data (meta, headings, links, images) |
on_page_content_parsing | Extract structured content from a page |
content_analysis_search | Search web content by keyword with sentiment and metrics |
content_analysis_summary | Get aggregated content metrics for a keyword |
content_analysis_phrase_trends | Track phrase popularity trends over time |
domain_analytics_technologies_domain_technologies | Detect technologies used on a domain |
domain_analytics_whois_overview | Get WHOIS registration data for a domain |
Run a comprehensive technical audit of one URL. Start with Lighthouse for performance scores, then get page optimization details, and optionally extract content structure.
Tool: on_page_lighthouse
Input: {
"url": "https://example.com/landing-page",
"for_mobile": true
}
Set for_mobile: true for mobile-first analysis (Google's default ranking signal). The response includes scores for performance, accessibility, best_practices, and seo (each 0-1, multiply by 100 for percentage). Drill into specific audits in the audits object for actionable recommendations.
Tool: on_page_instant_pages
Input: {
"url": "https://example.com/landing-page"
}
Returns page-level SEO signals: title tag, meta description, canonical URL, heading structure (h1-h6 counts), internal/external link counts, image alt text coverage, page size, load time, and HTTP status. Use this to identify missing meta tags, broken heading hierarchy, or oversized pages.
Tool: on_page_content_parsing
Input: {
"url": "https://example.com/landing-page"
}
Extracts structured content: paragraphs, headings, lists, and tables in clean format. Use this to analyze content quality, keyword density, or feed text into further analysis.
Understand how a topic is covered across the web — what content exists, overall sentiment, and trend direction.
Tool: content_analysis_search
Input: {
"keyword": "headless CMS comparison",
"search_mode": "as_is",
"limit": 50
}
Returns up to 50 pages matching the keyword with metadata: page type (ecommerce, news, blog, message-board, organization), sentiment (positive/negative/neutral), word count, date published, and social metrics. Use search_mode: "as_is" for exact phrase or "relevance" for semantic matching.
Tool: content_analysis_summary
Input: {
"keyword": "headless CMS comparison"
}
Returns aggregated metrics: total pages found, average sentiment score, content type distribution, and top domains covering the topic. Use this for a quick market snapshot before diving into individual pages.
Tool: content_analysis_phrase_trends
Input: {
"keyword": "headless CMS comparison",
"date_from": "2025-01-01"
}
The date_from parameter is required. Returns trend data showing how content publication volume for this phrase changed over time. Use this to identify rising topics, seasonal patterns, or declining interest. Set date_from to 6-12 months back for meaningful trends.
Discover the full technology stack of any domain — CMS, frameworks, analytics, CDN, hosting, email services, and more.
Tool: domain_analytics_technologies_domain_technologies
Input: {
"target": "example.com"
}
Returns categorized technology list: content management systems (WordPress, Shopify), JavaScript frameworks (React, Next.js), analytics (Google Analytics, Hotjar), CDN (Cloudflare, Fastly), hosting provider, advertising platforms, email services, and more. Each technology includes category, name, and version when detectable.
Use cases:
Get registration and ownership data for any domain.
Tool: domain_analytics_whois_overview
Input: {
"target": "example.com"
}
Returns WHOIS data: registrar, creation date, expiration date, updated date, name servers, registrant organization (when not privacy-protected), and domain status codes. Enriched with backlink summary stats when available.
Use cases:
| Score Range | Rating | Action |
|---|---|---|
| 90-100 | Good (green) | Maintain current optimizations |
| 50-89 | Needs Improvement (orange) | Address specific audit failures |
| 0-49 | Poor (red) | Prioritize immediate fixes |
Key Lighthouse audit categories:
Always check the audits object for specific failing items. Each audit has a score (0-1), title, and description explaining what to fix.
When interpreting content_analysis_search results:
| Metric | Values | Meaning |
|---|---|---|
sentiment_connotations | positive / negative / neutral | Overall tone of the content |
connotation_types | anger, happiness, sadness, fear, love, fun | Emotional tone breakdown |
page_types | ecommerce, news, blogs, message-boards, organization | Content category |
social_metrics | facebook, twitter shares | Content virality indicators |
word_count | integer | Content depth — higher often means more comprehensive |
spam_score | 0-100 | Quality indicator — lower is better |