seo-audit

SEO Audit Skill

A comprehensive SEO audit methodology that evaluates content for both traditional search engine optimization and modern AI/LLM visibility (GEO). Informed by Google's multi-stage ranking pipeline.

When to Use

• Auditing existing content for SEO performance
• Reviewing new content before publication
• Identifying optimization opportunities
• Assessing AI citation readiness
• Evaluating E-E-A-T signals
• Checking technical SEO elements
• Diagnosing why content isn't ranking
• Auditing new domains (sandbox considerations)

Google's Ranking Pipeline

Content passes through sequential evaluation gates. Understanding this pipeline informs what to audit and why.

Mustang → Topicality (T*) → NavBoost → Twiddlers
   ↓           ↓              ↓           ↓
 Initial   Query-match    User clicks   Final
 scoring   relevance      (13 months)   adjustments

Key Implications:

• Content must pass Mustang's quality gate before relevance even matters
• User behavior (NavBoost) accumulates over 13 months—patience required
• Two foundational pillars: Q* (site quality) and P* (popularity via Chrome data)
• Page potential is capped by domain's siteAuthority score

See assets/google-ranking-signals.yaml for complete signal reference.

Audit Framework

Phase 0: Domain & History Context

Before auditing content, assess domain-level factors that cap page potential:

Domain Authority Check:

• Established domain (>6 months) or new domain sandbox?
• Site-wide quality signals (clutterScore, ad density)
• Homepage authority inheritance for new pages
• Brand entity recognition (queriesForWhichOfficial)

URL History Assessment:

• Is this an established URL with history?
• URL changes reset accumulated trust (Google tracks last 20 versions)
• Evergreen URL structure (no dates unless news content)
• URL permanence strategy in place

Sandbox Awareness (New Domains/Pages):

Factor	Status	Impact
hostAge	New (<6mo) / Established	Domain-level sandbox
documentHistory	New URL / Has history	Page-level demotion
Graduation signals	Social, backlinks, engagement	Exit sandbox

If new domain: Set realistic expectations. Dual sandbox (host + document) requires consistent quality publishing, backlinks, and positive engagement over months.

Phase 1: Technical SEO Check

Evaluate foundational technical elements:

Page-Level Technical:

• URL structure (clean, descriptive, <60 chars, evergreen)
• Title tag (50-60 chars, keyword in first 30) → affects titlematchScore
• Meta description (150-160 chars, compelling CTA)
• H1 tag (single, matches topic)
• Header hierarchy (logical H1→H2→H3) → larger text weighted higher
• Image alt text (descriptive, keyword-relevant)
• Internal links (contextual, relevant)
• External links (authoritative sources)

Site-Level Technical:

• HTTPS enabled
• Mobile-friendly
• Page speed (<1.8s mobile)
• Schema markup present
• XML sitemap inclusion
• robots.txt accessibility

Entity & Trust Signals:

• Verifiable ownership/authorship (disconnected entity problem)
• Contact information accessible
• Organization schema linking to Knowledge Graph

Phase 2: Content Quality Assessment

Evaluate content depth and value. Google's contentEffort signal measures ML-assessed effort invested.

Content Completeness:

Factor	Check	Score	Signal
Topic coverage	Comprehensive vs. shallow	/10	contentEffort
Unique value	Original insights vs. rehash	/10	OriginalContentScore
Accuracy	Factual, verifiable	/10	Trust signals
Freshness	Current data/sources	/10	semanticDate
Depth	Expert-level detail	/10	contentEffort

Token Truncation Awareness: Google uses token limits—long documents may be truncated. Optimize for this:

• Critical information in first 20% of content (inverted pyramid)
• Key facts lead each section
• Paragraphs <120 words
• Front-load value, don't bury it

Readability:

• Reading level (target: Grade 8-10)
• Paragraph length (2-3 sentences ideal)
• Sentence variety
• Scannable formatting (bullets, headers)
• Visual aids (images, tables, diagrams)

Freshness Audit: Google evaluates freshness through three distinct methods:

• Explicit byline date (visible, accurate)
• URL date signals (avoid dates in evergreen URLs)
• Semantic freshness (are facts/sources current, not just timestamp?)

⚠️ Freshness spam detection: Changing timestamps without updating substance is detected via semanticDate comparison.

Phase 3: Keyword & Semantic Analysis

Assess keyword optimization. Affects Topicality (T*) stage scoring.

Primary Keyword:

• Present in title tag (first 30 chars ideal)
• In H1 and early H2s
• Natural density (0.5-1.5%)
• In meta description
• In first 100 words

Semantic Coverage:

• LSI keywords present
• Related entities covered (webrefEntities signal)
• Topic cluster alignment
• Question variations addressed
• Search intent match

Entity Optimization:

• Content associates with Knowledge Graph entities
• Clear entity relationships established
• Supports topical authority building

Phase 4: E-E-A-T Evaluation

Assess Experience, Expertise, Authority, Trust signals. These map directly to technical signals.

Experience Signals:

• First-hand experience indicated
• Case studies/examples included
• Original data/research
• Process documentation

Expertise Signals: (→ contentEffort, OriginalContentScore)

• Author credentials visible
• Technical accuracy
• Comprehensive coverage
• Expert quotes/interviews

Authority Signals: (→ siteAuthority, author attribute)

• Authoritative external citations
• Industry recognition
• Brand mentions
• Published research

Trust Signals:

• Contact information (disconnected entity fix)
• Privacy policy
• Editorial guidelines
• Reviews/testimonials
• Security indicators

Disconnected Entity Check: Sites without verifiable ownership, author info, and contact transparency trigger algorithmic distrust—even with high content quality.

Phase 5: AI/GEO Readiness

Assess content for LLM visibility:

Extractability:

• TL;DR or summary present (first 100 words)
• Paragraphs <120 words (token limit friendly)
• Clear topic sentences (lead with facts)
• Bullet lists for features
• Tables for comparisons
• FAQ section present

Fact-Density:

• Statistics with sources
• Specific numbers/dates
• Verifiable data points
• Expert quotes with attribution

Structure for AI:

• Question-based headers
• Direct answers near top (inverted pyramid)
• Logical information hierarchy
• Schema markup (FAQPage, HowTo)

Phase 6: User Behavior Signals

Google's NavBoost uses 13 months of aggregated click behavior. Audit for "good clicks" potential.

Click Quality Indicators:

• Title/meta accurately represent content (no clickbait)
• Content matches search intent (dwell time)
• Clear value proposition visible above fold
• Low bounce risk (content delivers on promise)

Engagement Factors:

Signal	Status	Improvement
Expected dwell time	Low/Med/High	Match intent better
Bounce risk	Low/Med/High	Clearer value prop
Return visit potential	Low/Med/High	Brand building

Output Format

SEO Audit Report

## SEO Audit Report

**Page:** [URL or filename]
**Date:** [Audit date]
**Overall Score:** X/100
**Domain Status:** [Established/New (sandbox considerations)]

### Executive Summary
[2-3 sentence overview including pipeline stage bottlenecks]

### Scores by Category

| Category | Score | Status | Key Signal |
|----------|-------|--------|------------|
| Domain/History | X/10 | [Status] | siteAuthority |
| Technical SEO | X/15 | [Status] | titlematchScore |
| Content Quality | X/25 | [Status] | contentEffort |
| Keyword Optimization | X/10 | [Status] | Topicality |
| E-E-A-T Signals | X/20 | [Status] | Trust signals |
| AI/GEO Readiness | X/10 | [Status] | Extractability |
| User Behavior | X/10 | [Status] | NavBoost |

### Pipeline Bottleneck Analysis
[Which pipeline stage is the primary blocker? Mustang quality? Topicality match? NavBoost signals?]

### Priority Issues (Fix First)

1. **[Issue]** - [Impact] - [Fix] - [Signal affected]
2. **[Issue]** - [Impact] - [Fix] - [Signal affected]
3. **[Issue]** - [Impact] - [Fix] - [Signal affected]

### Domain Context
[Sandbox status, authority inheritance, URL history]

### Technical SEO Findings
[Detailed findings with specific recommendations]

### Content Quality Findings
[contentEffort indicators, token optimization, freshness]

### Keyword Analysis
[Primary keyword performance, semantic gaps, entity coverage]

### E-E-A-T Assessment
[Specific signals present/missing, disconnected entity risk]

### AI Visibility Assessment
[GEO readiness score and improvements]

### User Behavior Optimization
[Click quality, dwell time, engagement improvements]

### Action Plan

**Immediate (This Week):**
- [ ] Action 1
- [ ] Action 2

**Short-term (This Month):**
- [ ] Action 1
- [ ] Action 2

**Ongoing (Sandbox Graduation):**
- [ ] Consistent quality publishing
- [ ] Social signal building
- [ ] Backlink acquisition
- [ ] User engagement optimization

Scoring Guide

90-100: Excellent - Minor optimizations only 70-89: Good - Some improvements needed 50-69: Needs Work - Significant gaps to address Below 50: Critical - Major overhaul required

New Domain Adjustment: Subtract 10-15 points for sandbox limitations. Focus on graduation signals.

Quick Audit Option

For faster audits, focus on:

1. Domain Context - Established or sandbox? URL history?
2. Title & Meta - Optimized for titlematchScore?
3. Content Quality - contentEffort indicators present?
4. E-E-A-T - Disconnected entity risk?
5. AI Ready - Inverted pyramid, extractable format?

Deliver top 5 issues with affected signals and fixes.

Signal Reference

For detailed signal documentation, see: assets/google-ranking-signals.yaml

Key signals to remember:

• titlematchScore - Title relevance to query
• contentEffort - ML-assessed content investment
• OriginalContentScore - Uniqueness (0-512 scale)
• semanticDate - Actual freshness of facts/sources
• siteAuthority - Domain-level authority cap
• chromeInTotal - Popularity via Chrome data