full-seo-audit

name	full-seo-audit
description	Audit my SEO, run an SEO audit, SEO score, SEO health check, full SEO analysis — comprehensive multi-category request. Performs a scoped 6-phase audit over the user's codebase plus a user-provided URL list (typically 5-10 URLs). Covers technical SEO, on-page SEO, content/E-E-A-T, schema, internal linking, and AI-extractability. Does NOT crawl the entire live site, does NOT measure Core Web Vitals numerically, does NOT infer backlinks — those require Path B MCP integrations. For single-area requests, route to the specialized skill instead.
argument-hint	[URL or path to audit] [--urls=url1,url2,...] [--non-interactive] [--resume <run-id>]
allowed-tools	Read Glob Grep Write Bash WebFetch WebSearch Agent

Full SEO Audit — Scoped Master Orchestrator

Coordinate a complete analysis across six phases over a defined audit surface (codebase + user-provided URL list), produce a unified score, and deliver a plain-English report with prioritized, actionable fixes.

This is a scoped audit, not a full-site crawl. Real full-site crawling requires a crawler MCP (Screaming Frog / Sitebulb / browser-based). Real Core Web Vitals require Lighthouse / PageSpeed Insights. This skill does the work that can be done honestly from static analysis + limited live fetches. The report explicitly lists what was and was not measured.

Every recommendation must explain WHY it matters in business terms, not just what to do. Write for a business owner who does not know what a canonical tag is.

Cross-model note

Works identically on current Opus / Sonnet / Haiku models. Opus/Sonnet batch codebase reads, URL fetches, and reference loads in parallel. Haiku may follow sequentially if parallel batching misbehaves.

Execution: parallel-first

• Phase 0 setup: all config/sitemap/robots reads independent — single batch
• Phase 1 technical: template Globs + config Reads + user URL fetches all independent — single batch
• Phase 2 on-page: per-page checks independent within a phase — batch
• Phase 3 schema: JSON-LD extraction per file independent — batch
• Phase 4 content/AEO: per-page scoring independent — batch
• Phase 5 internal linking: needs Phase 2's discovered page list — serialize start, parallelize per-page link extraction
• Phase 6 competitive: WebSearch queries independent — batch
• What to serialize, always: phase transitions (each phase may feed into the next phase's scope decision), user-approval gates in interactive mode

Capability Honesty

Read references/CAPABILITIES.md at the start. Key constraints:

• Cannot measure: numerical Core Web Vitals, keyword volumes, backlink counts, domain authority, actual AI citation rates, JS-rendered SPA content, full-site URL inventory
• Can measure: static-analysis findings across the user's codebase, observable findings from user-provided URLs (via WebFetch), SERP feature ownership (WebSearch), content structure quality, schema validity, code-level page-speed risk factors, internal linking graph for provided pages

Any category the user wants that requires unavailable infrastructure is reported in measurement_gaps[] with the Path B integration that would unlock it.

Mode Flags

• --non-interactive — Skip Phase 0 question gates. Use reasonable defaults, record unanswered context in awaiting_user_review. Auto-proceed through phase transitions. Emit trailing JSON with the final report path.
• --resume <run-id> — Load .seo/state/<run-id>.json and continue from the last saved phase.
• --urls=url1,url2,... — Explicit URL list to fetch (overrides the Phase 0 question)

Checkpoint & Resume

Save state to .seo/state/<run-id>.json at each phase boundary. Shared schema with other rad-seo multi-phase skills. See references/CAPABILITIES.md and the subagent-prompts for the full schema.

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Phase 0: Discovery

Gather required context before auditing. Ask the user and do not proceed until you have at least the codebase path or URL list:

1. Audit surface — Is this a codebase audit, URL-list audit, or both?
2. Codebase path — If applicable, the local path to the source code
3. URL list — If applicable, the live URLs to fetch (default limit ~10 to stay within budget; ask to confirm if more)
4. Business type — E-commerce, SaaS, local service, publisher, etc.
5. Target audience — Who they're trying to reach (geography, demographics, intent)
6. Top 3 competitors — URLs of the websites they compete with for search traffic
7. Primary business goal — Leads, sales, brand awareness, publishing — this weights recommendations

In --non-interactive mode, use whatever context was passed and record unanswered items in awaiting_user_review.

Save Phase 0 checkpoint.

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Phase 1: Technical SEO (20% weight)

Static analysis + limited live fetches for the technical foundation that search engines need to crawl, index, and serve the site properly.

Crawlability & Indexation (static analysis — scored fully)

Parallel batch: read robots.txt, XML sitemaps, template/layout files, framework config (next.config.*, astro.config.*, vite.config.*), .htaccess, _headers, vercel.json, netlify.toml.

• robots.txt exists? blocking important paths?
• XML sitemap at standard paths? referenced in robots? well-formed?
• Canonical tags present? self-referencing?
• noindex meta tags on pages that should be indexed?
• Redirect rules (configs): chains? loops?

Page-Speed Code-Level Risk Factors (static analysis — scored honestly, NOT CWV numbers)

Flag risk factors observable in code — NOT LCP/CLS/INP numbers, which require Lighthouse/PSI measurement:

• Large unoptimized images (.png/.jpg > threshold, missing width/height)
• Render-blocking scripts in <head> without defer/async
• Missing lazy loading on below-fold images
• Unminified JS/CSS in production
• Excessive third-party tags

The category's score reflects presence/absence of risk factors. If the user has a Lighthouse MCP available, use it for the real CWV score and merge; otherwise mark method as static-analysis in the JSON output.

Mobile Readiness (static analysis — scored fully)

• Viewport meta tag present
• Fixed-width elements that would break on small screens
• Tap target sizing

Security (static analysis — scored fully)

• HTTPS configuration (visible from URL list fetches)
• Mixed content (HTTP resources on HTTPS pages)
• Exposed sensitive paths (.env, .git, admin without protection)

URL Structure (static analysis — scored fully)

• Clean, descriptive URLs vs. query-string-heavy
• Trailing slash consistency
• 301 redirect hygiene (from config)

For deeper technical analysis, delegate to the technical-seo skill.

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Phase 2: On-Page SEO & E-E-A-T (15% weight)

Per-page analysis from codebase templates + URL fetches.

Title Tags & Meta Descriptions

• Every indexable page has a unique title (50-60 chars)
• Every indexable page has a unique meta description (120-160 chars)
• Titles contain primary keyword near the front
• Flag duplicates

Heading Structure

• Exactly one H1 per page, containing primary keyword
• Logical H1→H2→H3 hierarchy, no skipped levels
• Flag missing or multiple H1s

Content Quality Signals

• Flag thin content (< 300 words on competitive-term pages)
• Keyword stuffing patterns
• Image alt text present, descriptive, not filename gibberish

E-E-A-T Signals

• Author bylines and author bio pages
• About page, Contact page, Privacy Policy
• Trust signals: testimonials, reviews, certifications, credentials
• For YMYL (Your Money Your Life) sites, these are critical — flag missing signals as high priority

Why E-E-A-T matters: Google's quality raters evaluate these signals. Sites lacking them — especially in health, finance, or legal — face an uphill battle regardless of technical SEO quality.

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Phase 3: Content & AI-Extractability (20% weight)

Content quality + structural readiness for AI search engines. Uses the AI-extractability linter logic from aeo-optimizer Phase 1 (six structural dimensions).

Content Quality Scoring

For each key page: relevance to intent, depth, freshness, readability, unique value.

AI-Extractability Structure

• Question-format H2s (ratio)
• Direct-answer first-sentence pattern
• Quotable bold stats
• FAQ schema presence
• Comparison tables / structured formats
• Semantic chunking

Honest framing: this scores content's readiness to be cited by AI, not actual AI citation rate. See references/CAPABILITIES.md.

For deeper content analysis, delegate to on-page-optimizer or the content-auditor agent. For keyword gaps, delegate to keyword-discovery.

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Phase 4: Schema & Structured Data (10% weight)

Parallel-batch parse JSON-LD / Microdata / RDFa from templates and fetched pages.

Current Schema Audit

• Validate each schema block against schema.org
• Flag invalid, incomplete, deprecated types
• Check required properties per type

Missing Opportunities

By business type:

• All sites: Organization, WebSite, BreadcrumbList, SiteNavigationElement
• E-commerce: Product, Offer, AggregateRating, Review
• Local business: LocalBusiness, OpeningHoursSpecification, GeoCoordinates
• Publishers/blogs: Article, BlogPosting, Author (FAQPage only as an AI-parsing aid)
• Service businesses: Service (HowTo/FAQPage only as AI-parsing aids)
• Events: Event with proper date and location markup

Rich Snippet Potential

Flag pages close to qualifying for rich results but missing one or two properties — checking deprecations first (references/schema-types-guide.md): FAQ and HowTo rich results no longer exist (HowTo retired 2023, FAQ retired May 2026), so never list them as rich-result opportunities. Live opportunities: Product/Review stars, Article, Event, Recipe, VideoObject, Breadcrumb, JobPosting.

Why schema matters: Structured data does not directly boost rankings, but live rich-result types increase click-through rates, and clean entity markup aids AI parsing.

For detailed schema implementation, delegate to schema-architect.

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Phase 5: Internal Linking & Site Architecture (10% weight)

Orphan Pages

Pages in the sitemap or indexable but with zero internal links — invisible to search engines during crawling.

Link Distribution

• High-value keyword pages receive enough internal links
• Flag pages with 100+ outbound internal links (dilutes value)
• Identify pages with 1-2 internal links that should have more

Hub-and-Spoke Analysis

• Topic clusters: pillar (hub) → subtopic (spokes) → back to hub
• Flag disconnected content silos
• Recommend hub pages to create

Navigation & Depth

• Important pages reachable within 3 clicks from homepage
• Breadcrumb navigation present and logical
• Flag deep pages (4+ clicks) targeting important keywords

Why internal linking matters: One of few ranking factors entirely within the site owner's control. Distributes authority; tells search engines which pages matter most.

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Phase 6: Competitive Positioning (observational — feeds prioritization, no direct score weight)

Compare the site against competitors via observable signals. Uses the competitors identified in Phase 0.

Content Gaps

Topics and keywords competitors rank for that the user does not. Prioritize by observable signal strength + business relevance.

Link Gaps (observational only)

Note if competitors appear to have stronger backlink profiles via observable signals (e.g., press coverage, linkable assets). Do NOT report numerical backlink counts without Path B integration.

AI Citation Pattern Observation

Observe what content patterns competitors use that tend to earn AI citations. This is pattern observation, NOT a measurement of their actual citation rates.

Feature Comparison

• Schema markup coverage across competitors
• Code-level page-speed risk factors observable from fetched HTML
• Rich results competitors earn that the audited site does not

For deeper competitive analysis, delegate to competitor-intelligence or the competitor-spy agent.

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Scoring System

Read references/audit-scoring-rubric.md for the full category weights, severity deductions, A-F scale, and scoring methodology.

Important: categories whose measurement requires unavailable infrastructure are marked method: not-measured and excluded from the overall weighted score — NEVER fabricated. The report explicitly lists those gaps in the measurement_gaps section.

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Report Generation

After completing all six phases, produce the audit report. Write in plain English for a non-technical business owner.

# SEO Audit Report: [Website]
## Date: [date]
## Audit Scope: [codebase | URL list | both] — [pages audited]
## Overall Score: [X]/100 (Grade: [A-F])
## Measurement Gaps: [list categories requiring Path B — their Path B unlock]

### Executive Summary
[2-3 paragraphs. Lead with the biggest finding. Summarize what works, what needs urgent attention,
and the single highest-impact action. Name the measurement gaps honestly.]

### Score Breakdown
| Category | Score | Grade | Method | Critical | Warnings | Opportunities |
|---|---|---|---|---|---|---|
| Technical SEO | /100 | | static-analysis | | | |
| On-Page SEO | /100 | | static-analysis | | | |
| Content & E-E-A-T | /100 | | static-analysis | | | |
| Schema & Structured Data | /100 | | static-analysis | | | |
| Internal Linking | /100 | | graph-built | | | |
| Page Speed (code-level risk) | /100 | | static-analysis | | | |
| Page Speed (CWV numbers) | N/A | | not-measured (needs Lighthouse MCP) | | | |
| Mobile Usability | /100 | | static-analysis | | | |
| AI-Extractability | /100 | | static-analysis | | | |
| **Overall (Weighted, measured categories only)** | **/100** | | | | | |

### Critical Issues (Fix Immediately)
[Per issue: impact, category, what's wrong, why it matters in business terms, how to fix with Claude Code command]

### Warnings (Fix Within 30 Days)
[Per issue: same format]

### Opportunities (Nice to Have)
[Per issue: same format]

### 30/60/90 Day Roadmap
#### Days 1-30: Foundation Fixes
#### Days 31-60: Content & Authority
#### Days 61-90: Growth & Competitive Edge

### AI-Extractability Score
[What it means: "measures how structurally ready your content is to be cited by AI engines.
Does NOT measure actual AI citations — that would require Path B MCP integration."
Then: current score, top 3 things helping, top 3 things hurting, specific conversion recommendations.]

### Measurement Gaps (What This Audit Did NOT Measure)
[For each gap: what you wanted, why it requires external infrastructure, which Path B MCP
would unlock it.]

### Next Steps
- Re-audit in: [30/60/90 days depending on severity]
- Ongoing monitoring: [what to track weekly/monthly — only things you can actually measure]
- Quick wins completed during audit: [list fixes applied]
- Path B integrations to consider: [ranked list of MCPs that would unlock measurement gaps]
- Specialist skills to run next: [list of relevant rad-seo skills]

---

Execution Rules

1. Complete all 6 phases. If a phase has no issues, say so and score accordingly.
2. Fix simple issues on the spot. Codebase access + missing meta description or broken schema? Fix it during the audit. Note under "Quick wins completed during audit."
3. Be specific, not generic. "The /pricing page has no meta description — here's the exact command to add one" beats "improve meta descriptions."
4. Rank by impact vs. effort. Quick win > Strategic > Fill-in > Deprioritize.
5. Provide exact commands. Every fix includes a Claude Code command or copy-paste file edits.
6. Explain business impact. "LCP risk factor: unoptimized 3MB hero image" → "This hero image likely delays the main page paint noticeably on mobile. Compress to < 200KB."
7. Be honest about measurement gaps. Never fabricate a number. Always surface the Path B unlock.
8. Respect the report template. Keep reports consistent so they're comparable over time.

---

Output JSON (for --non-interactive)

{
  "audit_complete": true,
  "run_id": "string",
  "audit_scope": "codebase | urls | both",
  "overall_score": 0,
  "overall_grade": "A | B | C | D | F",
  "report_path": "seo-audit-report.md",
  "measurement_gaps": [
    {"category": "string", "path_b_integration": "string"}
  ],
  "critical_count": 0,
  "warning_count": 0,
  "opportunity_count": 0,
  "quick_wins_applied": 0,
  "escalation_required": false,
  "awaiting_user_review": ["string"]
}

---

Cross-Skill Delegation Reference

Situation	Delegate To	What It Does
Complex crawl issues, redirect chains, server config	technical-seo	Deep technical analysis on static + config surface
Need keyword targets	keyword-discovery	Keyword ideation + intent (volumes require Path B)
Content rewriting	on-page-optimizer	Content quality + AEO conversion
Schema needs writing or fixing	schema-architect	JSON-LD implementation + validation
Detailed competitor breakdown	competitor-intelligence	Observable competitive research
Ongoing scheduled auditing	full-seo-audit	Run on a cadence

Always complete the full audit first. Delegate to specialists for implementation, not for the audit itself.