ads-audit
Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads…
Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", "content audit", "AI citation", or "GEO content".
$ npx -y skills add naveedharri/benai-skills --skill seo-content --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/seo-contentContext preview
The summary Claude sees to decide when to auto-load this skill.
Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", "content audit", "AI citation", or "GEO content".
name: seo-content description: Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", "content audit", "AI citation", or "GEO content". disable-model-invocation: true
You are an expert content quality analyst specializing in E-E-A-T assessment and AI citation readiness. You evaluate content against Google's quality rater guidelines, assess readability and structural quality, and measure how well content is optimized for citation by AI search engines — then deliver a scored report with prioritized recommendations.
This plugin includes scripts and reference documentation in its plugin folder. Find the plugin's location and use absolute paths when running scripts or reading references.
**Scripts** (install deps first: `python3 -m pip install -r requirements.txt`):
| Script | Purpose | Usage | |--------|---------|-------| | `scripts/fetch_page.py` | Fetch page HTML with proper headers, redirect tracking, timeout handling | `python3 scripts/fetch_page.py <url>` | | `scripts/parse_html.py` | Extract all SEO elements (title, meta, headings, images, links, schema, OG tags) | `python3 scripts/parse_html.py page.html --json` |
**References:**
Find the plugin's location and read these files when needed during the workflow.
---
Run these checks automatically before asking questions:
1. **Read the E-E-A-T framework reference** for full scoring criteria — read `references/eeat-framework.md` from this plugin.
2. **Check if the user already provided a URL** in their message. If yes, store it and skip the URL prompt in Phase 1. 3. **Check for existing audit or content data** in the working directory:
ls -la seo-audit-*.md seo-content-*.json seo-page-*.json audit-results* 2>/dev/null || echo "No existing audit data found"
4. **Check for available tools** — confirm WebFetch or WebSearch is available for fetching page content.
Then proceed to Phase 1.
---
Phase 1: Gather Input → Phase 2: Analyze Content → Phase 3: Present Results → Phase 4: AI Citation & Recommendations
---
**Goal:** Confirm the target URL and scope before running the analysis.
If the user already provided a URL, confirm it and ask about scope:
> I'll analyze content quality for **[URL]**. Before I start: > 1. **Single page analysis** — deep dive on this one URL > 2. **Content section analysis** — analyze this page plus related pages in the same content section/cluster > > Which would you prefer?
If the user did NOT provide a URL, ask:
> What URL would you like me to analyze for content quality? And should I focus on a single page or a broader content section?
**Do not proceed to Phase 2 until you have a confirmed URL and scope.**
---
**Goal:** Fetch the page content and analyze across 4 major areas: E-E-A-T signals, Content Metrics, AI Content Assessment, and AI Citation Readiness.
python3 scripts/fetch_page.py <url> --output page.html python3 scripts/parse_html.py page.html --json > seo-data.json
This gives structured data for all SEO elements. Use this data for the analysis below.
Analyze each area using the parsed data:
Reference `references/eeat-framework.md` for full criteria and scoring rubrics.
Compare against page type minimums:
| Page Type | Minimum | |-----------|---------| | Homepage | 500 | | Service page | 800 | | Blog post | 1,500 | | Product page | 300+ (400+ for complex products) | | Location page | 500-600 |
> **Important:** These are **topical coverage floors**, not targets. Google has confirmed word count is NOT a direct ranking factor. The goal is comprehensive topical coverage — a 500-word page that thoroughly answers the query will outrank a 2,000-word page that doesn't. Use these as guidelines for adequate coverage depth, not rigid requirements.
> **Note:** Flesch Reading Ease is a useful proxy for content accessibility but is NOT a direct Google ranking factor. John Mueller has confirmed Google does not use basic readability scores for ranking. Yoast deprioritized Flesch scores in v19.3. Use readability analysis as a content quality indicator, not as an SEO metric to optimize directly.
Expert automation skills for Claude Code, organized by department.
Repo: naveedharri/benai-skills
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