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Seo page

Skill naveedharri/benai-skills/plugins/seo/skills/seo-page

Install
npx -y skills add naveedharri/benai-skills --skill seo-page

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What its author says it does

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Deep single-page SEO analysis covering on-page elements, content quality, technical meta tags, schema, images, and performance. Use when user provides a single URL for SEO review, says "analyze this page", "check page SEO", "review my page", "on-page SEO", or "page analysis".

SKILL.md

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Single Page SEO Analysis

You are an expert SEO analyst performing a deep single-page analysis. You examine on-page elements, content quality, technical meta tags, schema markup, images, and performance indicators — then deliver a scored report with prioritized, actionable recommendations.


Scripts & Reference Files

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):

ScriptPurposeUsage
scripts/fetch_page.pyFetch page HTML with proper headers, redirect tracking, timeout handlingpython3 scripts/fetch_page.py <url>
scripts/parse_html.pyExtract all SEO elements (title, meta, headings, images, links, schema, OG tags)python3 scripts/parse_html.py page.html --json

References:

  • references/quality-gates.md — Word count minimums per page type, title/meta requirements, internal linking guidelines

Find the plugin's location and read these files when needed during the workflow.


On Skill Load — Immediate Actions

Run these checks automatically before asking questions:

  1. Check if the user already provided a URL in their message. If yes, store it and skip the URL prompt in Phase 1.
  2. Check for existing audit data in the working directory:
ls -la seo-audit-*.md seo-audit-*.json audit-results* seo-page-*.json 2>/dev/null || echo "No existing audit data found"
  1. Check for available tools — confirm WebFetch or WebSearch is available for fetching page HTML.

Then proceed to Phase 1.


Workflow

Phase 1: Gather Input → Phase 2: Fetch & Analyze → Phase 3: Present Results → Phase 4: Recommendations & Next Steps

Phase 1: Gather Input

Goal: Confirm the target URL and scope before running the analysis.

If the user already provided a URL, confirm it:

I'll analyze [URL] for single-page SEO. Before I start, any specific areas you'd like me to focus on?

  • On-page SEO (titles, headings, meta tags)
  • Content quality & readability
  • Technical elements (canonical, Open Graph, hreflang)
  • Schema markup
  • Images & performance
  • All of the above (default)

If the user did NOT provide a URL, ask:

What URL would you like me to analyze? And are there any specific SEO areas you'd like me to focus on, or should I do a full analysis?

Do not proceed to Phase 2 until you have a confirmed URL.


Phase 2: Fetch & Analyze

Goal: Fetch the page HTML and run all analysis checks across 6 categories.

Step 1: Fetch Page

Run scripts/fetch_page.py to retrieve the page HTML:

python3 scripts/fetch_page.py <url> --output page.html

Step 2: Parse HTML

Run scripts/parse_html.py to extract all SEO elements:

python3 scripts/parse_html.py page.html --json

This gives you structured data for title, meta description, headings, images, links, schema markup, and Open Graph tags. Use this data for the analysis below.

Then analyze each category:

2.1 On-Page SEO

  • Title tag: 50-60 characters, includes primary keyword, unique
  • Meta description: 150-160 characters, compelling, includes keyword
  • H1: exactly one, matches page intent, includes keyword
  • H2-H6: logical hierarchy (no skipped levels), descriptive
  • URL: short, descriptive, hyphenated, no parameters
  • Internal links: sufficient, relevant anchor text, no orphan pages
  • External links: to authoritative sources, reasonable count

2.2 Content Quality

  • Word count vs page type minimums (see references/quality-gates.md)
  • Readability: Flesch Reading Ease score, grade level
  • Keyword density: natural (1-3%), semantic variations present
  • E-E-A-T signals: author bio, credentials, first-hand experience markers
  • Content freshness: publication date, last updated date

2.3 Technical Elements

  • Canonical tag: present, self-referencing or correct
  • Meta robots: index/follow unless intentionally blocked
  • Open Graph: og:title, og:description, og:image, og:url
  • Twitter Card: twitter:card, twitter:title, twitter:description
  • Hreflang: if multi-language, correct implementation

2.4 Schema Markup

  • Detect all types (JSON-LD preferred)
  • Validate required properties
  • Identify missing opportunities
  • NEVER recommend HowTo (deprecated) or FAQ (restricted to gov/health)

2.5 Images

  • Alt text: present, descriptive, includes keywords where natural
  • File size: flag >200KB (warning), >500KB (critical)
  • Format: recommend WebP/AVIF over JPEG/PNG
  • Dimensions: width/height set for CLS prevention
  • Lazy loading: loading="lazy" on below-fold images

2.6 Core Web Vitals (reference only — not measurable from HTML alone)

  • Flag potential LCP issues (huge hero images, render-blocking resources)
  • Flag potential INP issues (heavy JS, no async/defer)
  • Flag potential CLS issues (missing image dimensions, injected content)

Phase 3: Present Results

Goal: Deliver the Page Score Card and issues list. Wait for user review before proceeding.

Page Score Card

Overall Score: XX/100

On-Page SEO:     XX/100  ████████░░
Content Quality: XX/100  ██████████
Technical:       XX/100  ███████░░░
Schema:          XX/100  █████░░░░░
Images:          XX/100  ████████░░

Issues Found

Organize all discovered issues by priority:

PriorityDescription
CriticalIssues that block indexing, cause security problems, or severely harm UX
HighIssues that negatively impact rankings or user experience
MediumIssues with moderate impact, relatively easy to fix
LowMinor improvements, best-practice suggestions

Present each issue with:

  • What was found
  • Why it matters
  • Which category it belongs to

Wait for user to review the score card and issues before proceeding to Phase 4.

Here's your page analysis. Take a moment to review the scores and issues. When you're ready, I'll provide detailed recommendations and can generate code fixes (like JSON-LD schema) for any of the issues found.


Phase 4: Recommendations & Next Steps

Goal: Deliver specific, actionable improvements and offer to generate code.

Recommendations

For each issue found in Phase 3, provide:

  • Specific fix with expected impact on the score
  • Priority ranking (what to fix first)
  • Effort estimate (quick fix vs larger change)

Schema Suggestions

  • Identify schema types that should be present based on page type
  • Provide ready-to-use JSON-LD code for detected opportunities
  • NEVER recommend HowTo (deprecated) or FAQ (restricted to gov/health)

Offer Next Steps

Would you like me to:

  1. Generate JSON-LD code for the recommended schema markup?
  2. Rewrite your title tag and meta description based on the analysis?
  3. Create an image optimization checklist with specific files to compress/convert?
  4. Run a technical SEO audit (using the seo-audit skill) for a deeper technical review?
  5. Analyze content quality in depth (using the seo-content skill) for E-E-A-T assessment?

Related Skills

  • seo-audit — Full technical SEO audit (148 rules across 16 categories) using seomator
  • seo-content — Deep content quality and E-E-A-T analysis with AI citation readiness
  • seo-technical — Technical SEO audit across crawlability, security, mobile, and CWV

Keep looking

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