Page Seo Analysis
Analyze SEO for a single page.
Marketing teams lose hours to ad-hoc, inconsistent page seo analysis work — Analyze SEO for a single page. Use when: auditing on-page signals, schema, content quality, E-E-A-T, or AI search readiness. This playbook turns the process into a repeatable, brand-aware workflow.
Who it's for: SEO specialists, content marketers, technical SEO leads, growth marketers
Example
"Run /page-seo-analysis for our brand" → Page Seo Analysis workflow output with brand context, structured inputs captured, process steps executed, and a complete deliverable ready for review.
CLAUDE.md Template
New here? 3-minute setup guide → | Already set up? Copy the template below.
# Page Seo Analysis
# /dm:page-analysis
## Purpose
Deep single-page SEO analysis — examines everything about one URL across all ranking dimensions. More granular than a site-wide audit. Use for landing page optimization, content refresh prioritization, or pre-publish quality checks.
## Input Required
- **URL**: The specific page to analyze
- **Target keyword**: Primary keyword this page should rank for (optional — can be inferred)Get new playbooks like this one
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What This Does
Deep single-page SEO analysis — examines everything about one URL across all ranking dimensions. More granular than a site-wide audit. Use for landing page optimization, content refresh prioritization, or pre-publish quality checks.
Quick Start
Step 1: Create a Project Folder
Create a dedicated folder for this workflow (e.g. ~/marketing/page-seo-analysis).
Step 2: Download the Template
Click Download above and save the file as CLAUDE.md in that folder.
Step 3: Run the Workflow
Open the folder in Claude Code and describe your goal. Claude will prompt you for any missing inputs, follow the structured process, and produce a complete deliverable.
Inputs You'll Need
- URL: The specific page to analyze
- Target keyword: Primary keyword this page should rank for (optional — can be inferred)
- Competitors: 1-3 competitor pages targeting the same keyword (optional)
How It Works
- Load brand context: Read active brand profile. Load brand guidelines if available.
- Fetch and parse page: Retrieve full HTML, extract all signals.
- Title tag analysis: Character count (50-60 chars ideal), keyword placement, brand inclusion, uniqueness, click-worthiness.
- Meta description analysis: Character count (150-160 chars), keyword inclusion, CTA presence, uniqueness.
- Heading hierarchy: H1 presence and uniqueness, H2-H6 logical structure, keyword distribution across headings.
- Content depth analysis: Word count, reading level, topic coverage completeness, keyword density (target 1-2%), semantic keyword usage, content freshness (last modified date).
- E-E-A-T signals: Author byline and bio, credentials, first-hand experience indicators, citations and sources, about page link, contact information.
- Schema markup detection: JSON-LD, Microdata, RDFa — validate against Google's supported types, check for deprecations (HowTo deprecated Sept 2023, FAQ restricted to gov/health Aug 2023, SpecialAnnouncement deprecated July 2025), suggest missing schema opportunities.
- Image audit: Alt text, dimensions, format, lazy loading, fetchpriority on LCP image (see image-seo-audit skill for full methodology).
- Internal linking: Inbound links to this page, outbound links from this page, anchor text quality, orphan page check.
- Technical signals: Canonical tag, robots directives, mobile viewport, HTTPS, page speed indicators, Core Web Vitals.
- AI search readiness: Entity consistency, citation-worthiness, structured answer formatting, concise answer blocks for featured snippets.
- Competitor comparison (if provided): Side-by-side analysis of word count, schema, headings, E-E-A-T signals vs competitor pages.
What You Get
Page SEO Score: XX/100
| Dimension | Score | Priority Issues |
|---|---|---|
| Title & Meta | /10 | ... |
| Content Depth | /10 | ... |
| E-E-A-T | /10 | ... |
| Schema Markup | /10 | ... |
| Images | /10 | ... |
| Internal Links | /10 | ... |
| Technical | /10 | ... |
| AI Readiness | /10 | ... |
- Specific, actionable recommendations for each dimension
- Exact replacement title tags and meta descriptions (with character counts)
- Missing schema markup JSON-LD code (ready to implement)
- Content gaps vs competitors
- Quick wins vs strategic improvements