When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Also covers generative-engine visibility (GEO/AEO): "AI Overviews," "AI search," "not showing up in ChatGPT," "get cited by AI," "GEO," "answer engine optimization," "llms.txt," "AI crawlers," "GPTBot," or "ClaudeBot." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. In AKILI-SPECS projects, /akili-seo loads this skill in its audit phase.
Instrucciones de origen · Vista previa de solo lectura
name
seo-audit
description
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Also covers generative-engine visibility (GEO/AEO): "AI Overviews," "AI search," "not showing up in ChatGPT," "get cited by AI," "GEO," "answer engine optimization," "llms.txt," "AI crawlers," "GPTBot," or "ClaudeBot." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. In AKILI-SPECS projects, /akili-seo loads this skill in its audit phase.
SEO Audit
You are an expert in search engine optimization. Your goal is to identify SEO issues and provide actionable recommendations to improve organic search performance.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before auditing, understand:
Site Context
What type of site? (SaaS, e-commerce, blog, etc.)
What's the primary business goal for SEO?
What keywords/topics are priorities?
Current State
Any known issues or concerns?
Current organic traffic level?
Recent changes or migrations?
Scope
Full site audit or specific pages?
Technical + on-page, or one focus area?
Access to Search Console / analytics?
Audit Framework
Schema Markup Detection Limitation
web_fetch and curl cannot reliably detect structured data / schema markup.
Many CMS plugins (AIOSEO, Yoast, RankMath) inject JSON-LD via client-side JavaScript — it won't appear in static HTML or web_fetch output (which strips <script> tags during conversion).
To accurately check for schema markup, use one of these methods:
Browser tool — render the page and run: document.querySelectorAll('script[type="application/ld+json"]')
Screaming Frog export — if the client provides one, use it (SF renders JavaScript)
Reporting "no schema found" based solely on web_fetch or curl leads to false audit findings — these tools can't see JS-injected schema.
Priority Order
Crawlability & Indexation (can Google find and index it?)
Technical Foundations (is the site fast and functional?)
On-Page Optimization (is content optimized?)
Content Quality (does it deserve to rank?)
Authority & Links (does it have credibility?)
GEO is a layer, not a sixth priority. Generative-engine visibility (AI Overviews, ChatGPT,
Perplexity) is applied on top of pages that already rank or can — roughly three quarters of AI
Overview citations come from pages already in the top 10. Never trade a fix from the list above for a
GEO fix. Run the priority order first, then apply the GEO section.
Technical SEO Audit
Crawlability
Robots.txt
Check for unintentional blocks
Verify important pages allowed
Check sitemap reference
Disallow is not noindex. A disallowed URL can still be indexed (from external links) and will show as "Indexed, though blocked by robots.txt". To remove a page from the index you must let Google crawl it and serve noindex — blocking it prevents Google from ever seeing the directive. A noindex line inside robots.txt is unsupported and ignored.
AI crawler directives (see GEO reference for the full agent table)
Distinguish training agents (GPTBot, ClaudeBot, Google-Extended) from retrieval agents (OAI-SearchBot, Claude-SearchBot, PerplexityBot) and user-triggered fetchers (ChatGPT-User, Claude-User, Perplexity-User)
High-impact finding: a blanket AI-bot block removes the site from AI answers as well as from training corpora. Confirm the client's intent before treating either state as correct
Google-Extended is a robots.txt token only — it never appears in logs, and blocking it does not affect Googlebot, Search, or AI Overviews
Where the requirement is genuine prevention rather than preference, note that robots.txt is advisory and escalate to WAF/bot management
XML Sitemap
Exists and accessible
Submitted to Search Console
Contains only canonical, indexable URLs
Updated regularly
Proper formatting
Site Architecture
Important pages within 3 clicks of homepage
Logical hierarchy
Internal linking structure
No orphan pages
Crawl Budget Issues (for large sites)
Parameterized URLs under control
Faceted navigation handled properly
Infinite scroll with pagination fallback
Session IDs not in URLs
Indexation
Index Status
site:domain.com check
Search Console coverage report
Compare indexed vs. expected
Indexation Issues
Noindex tags on important pages
Canonicals pointing wrong direction
Redirect chains/loops
Soft 404s
Duplicate content without canonicals
Canonicalization
All pages have canonical tags
Self-referencing canonicals on unique pages
HTTP → HTTPS canonicals
www vs. non-www consistency
Trailing slash consistency
Site Speed & Core Web Vitals
Core Web Vitals
LCP (Largest Contentful Paint): < 2.5s
INP (Interaction to Next Paint): < 200ms
CLS (Cumulative Layout Shift): < 0.1
Speed Factors
Server response time (TTFB)
Image optimization
JavaScript execution
CSS delivery
Caching headers
CDN usage
Font loading
Tools
PageSpeed Insights
WebPageTest
Chrome DevTools
Search Console Core Web Vitals report
Mobile-Friendliness
Responsive design (not separate m. site)
Tap target sizes
Viewport configured
No horizontal scroll
Same content as desktop
Mobile-first indexing readiness
Security & HTTPS
HTTPS across entire site
Valid SSL certificate
No mixed content
HTTP → HTTPS redirects
HSTS header (bonus)
URL Structure
Readable, descriptive URLs
Keywords in URLs where natural
Consistent structure
No unnecessary parameters
Lowercase and hyphen-separated
International SEO & Localization
Check when the site serves multiple languages or regions. Misconfigurations can suppress indexing of entire locale variants or drag down site-wide quality signals. See International SEO reference for evidence and source URLs.
Hreflang
Three equivalent placement methods: HTML <link> in <head>, HTTP Link headers, XML sitemap <xhtml:link>. If using multiple, they must agree -- conflicting signals cause Google to drop that pair. For 10+ locales, prefer sitemap-based (no page weight, no per-request cost).
Check for:
Self-referencing entry on every page (page must include itself in the hreflang set)
Reciprocal links (if A points to B, B must point back to A -- or both are ignored)
Valid codes: ISO 639-1 language + optional ISO 3166-1 Alpha 2 region (e.g., en, en-GB -- never en-UK)
x-default present, pointing to fallback page (language selector or default locale)
All target URLs return 200, are indexable, and match their canonical URL
No duplicate language-region codes pointing to different URLs
Common errors: Missing self-referencing entry (all hreflang ignored). No return tag / one-directional (pair dropped). Invalid codes like en-UK (use en-GB). Hreflang target is non-canonical, 404, or blocked (cluster discarded). HTML and sitemap annotations disagree (conflicting pair dropped).
At scale:<xhtml:link> children don't count toward 50K URL sitemap limit, but the 50MB file size limit becomes the bottleneck (plan 2K-5K URLs per file with full hreflang). Focus hreflang on pages receiving wrong-language traffic -- not required on every page. For Bing: supplement with <html lang> and <meta http-equiv="content-language"> (Bing treats hreflang as a weak signal).
Canonicalization for Multilingual Sites
Each locale page must self-canonical (e.g., /ar/page canonicals to /ar/page)
Never cross-locale canonical (French to English) -- suppresses the non-canonical locale entirely
Canonical URL must appear in the hreflang set -- if not, all hreflang is ignored
Canonical overrides hreflang when they conflict
Protocol/domain must be consistent across canonical, hreflang, and sitemap (https + same domain variant)
Paginated locale pages: self-referencing canonical per page (never canonical page 2+ to page 1)
Common mistakes: all locales canonical to English (kills indexing), canonical URL not in hreflang set (silently ignored), protocol mismatch between canonical and hreflang, CMS setting deep page canonical to homepage.
International Sitemaps
Check for:
xmlns:xhtml namespace on <urlset>, each <url> includes <xhtml:link> for all locales including itself
x-default alternate included; all URLs absolute (full protocol + domain)
Sitemap index in Search Console and robots.txt; split by content type, not by locale
Next.js caveat:alternates.languages does NOT auto-include a self-referencing <xhtml:link> for the <loc> URL -- you must add the current locale explicitly.
Locale URL Structure
Recommended: Subdirectories (/en/, /ar/). Acceptable: Subdomains or ccTLDs. Not recommended: URL parameters (?lang=en).
Check for:
Consistent locale prefix strategy; all locales prefixed (hiding locale from URLs prevents Google from distinguishing versions)
Root URL handled as x-default with redirect, or serves default locale content
No IP/Accept-Language content negotiation (Googlebot: US IPs, no Accept-Language header)
Trailing slash + case consistency across locale paths, canonicals, hreflang, and sitemaps
301 redirects from non-canonical format to canonical
Note: Google's International Targeting report in Search Console is deprecated. Geotargeting relies on hreflang, content signals, and linking patterns.
Content Quality Across Locales
Translation quality:
AI-translated content is not inherently spam (Google's 2025 stance), but scaled low-value translations can trigger scaled content abuse policy
Google uses visible content to determine language -- translate ALL page content (title, description, headings, body), not just boilerplate
Translating only template/nav while main content stays in original language creates duplicates
Thin locale pages:
Helpful content system is site-wide -- many thin locale pages can suppress rankings for strong pages too
Don't noindex thin locales (wastes crawl budget) or cross-locale canonical (conflicts with hreflang)
Best approach: don't create locale pages you cannot make genuinely helpful
Check for:
All locale pages have fully translated main content (not just UI chrome)
No near-identical content across locales ("Duplicate, Google chose different canonical" in GSC)
Hreflang only for locales with genuine content and search demand
Localized signals: currency, phone format, addresses where applicable
Read the Schema Markup Detection Limitation above before auditing this — a static fetch cannot
see JS-injected JSON-LD, and reporting "no schema found" from curl output is a false finding.
Check for:
Correct type for the page's purpose (Article/TechArticle, Product, FAQPage, HowTo, BreadcrumbList, Organization, Person, SoftwareApplication, LocalBusiness)
Validates without errors in the Rich Results Test
Markup matches visible page content — invisible or contradictory markup is a spam-policy violation, not an optimization
dateModified present and truthful on content that changes
@id used consistently so nodes can reference each other instead of being duplicated
One coherent graph per page rather than several disconnected islands
Common issues:
Required properties missing, so the type is ineligible for rich results
FAQPage markup on content that is not a genuine Q&A
Schema describing content the user cannot see
Stale dateModified auto-set to build time on unchanged pages
Duplicate Organization nodes on every page with no shared @id
Structured data also has a measurable association with citation in generative answers — see the
GEO section.
Content Quality Assessment
E-E-A-T Signals
Experience
First-hand experience demonstrated
Original insights/data
Real examples and case studies
Expertise
Author credentials visible
Accurate, detailed information
Properly sourced claims
Authoritativeness
Recognized in the space
Cited by others
Industry credentials
Trustworthiness
Accurate information
Transparent about business
Contact information available
Privacy policy, terms
Secure site (HTTPS)
Content Depth
Comprehensive coverage of topic
Answers follow-up questions
Better than top-ranking competitors
Updated and current
User Engagement Signals — diagnostic only, not ranking factors
Google does not use analytics engagement metrics as ranking factors. John Mueller: "We don't use
bounce rate in search rankings." Gary Illyes: "we don't use analytics/bounce rate in search
ranking." Google has denied this for roughly a decade.
Never write a finding that says "improve bounce rate to improve rankings" — it is a causal claim
Google has explicitly denied, and it damages the credibility of the correct findings next to it.
Use these metrics the other way round: as diagnostics that localize a content problem, whose fix
is the content itself.
Metric
Read it as
High exit rate on a ranking page
Possible intent mismatch — the page ranks for a query it does not answer
Very low time on page for long-form content
Content may be unscannable, or the answer is buried
Pages per session
Internal linking and topical-cluster coverage signal
Return visits
Brand and content-quality signal (correlates with, does not cause, ranking)
Visibility inside AI-generated answers — Google AI Overviews / AI Mode, ChatGPT, Claude, Perplexity —
rather than in a ranked list of links. See the GEO reference for the measured
evidence, source tiers, and the full AI-crawler agent table.
GEO layers on top of ranking; it does not replace it. Roughly three quarters of AI Overview
citations come from pages already in the top 10. Audit the priority order first.
What measurably works
Peer-reviewed measurement (GEO-bench, KDD 2024: ~10,000 queries across nine datasets) found the
largest visibility gains come from evidence, not markup:
Finding to raise
Measured effect
Claims lack verifiable statistics with named sources
~30–40% gain when added
No credible quotations where the topic supports them
~30–40%
No outbound citations to reliable sources
~30–40%
Poor fluency / readability
~15–30%
Keyword stuffing present
Negligible or negative — treat as a defect, not a tactic
Gains are largest for content that is visible but not dominant (up to +115.1% at position 5), which
is most audit subjects.
The self-containment test
Generative engines extract passages, not pages. For each passage the page wants cited, ask:
does this paragraph still make sense lifted out with no surrounding context?
Anaphora that depends on the previous paragraph ("this approach", "as mentioned above", "the former")
breaks extraction. This is the most common GEO defect on otherwise well-optimized pages, and no
classic on-page check catches it.
Also require: a definitional sentence ("X is a Y that does Z.") at first use of every term the
page wants to own, and a Q&A block with the question as the heading and the direct answer in the
first sentence.
Checks
Verifiable statistics, quotations, and outbound citations present
Target passages pass the self-containment test
Definitional sentence at first use of each ownable term
Entity resolvable in one sentence (what it is, who made it); Person/Organization + sameAs
dateModified exposed; no stale visible version numbers or dates (fresh content is cited far more often)
JSON-LD present and valid (see Structured Data above)
robots.txt separates training agents from retrieval agents, matching the client's stated intent
No unverifiable numeric or superlative claims in <title>, meta description, or JSON-LD
Do not raise these
Missing llms.txt. Adoption is ~8.7% of the top 1,000 domains, ~40% of existing files are
empty plugin stubs, no major AI crawler has committed to consuming it, crawler logs show the
retrieval agents skip it, and in one citation model removing the variable improved accuracy. It
has a legitimate use as business-to-agent context for IDE agents and MCP servers — recommend it on
developer-experience grounds or not at all, never as a visibility tactic.
"Improve bounce rate to rank better." See User Engagement Signals above.
Common Issues by Site Type
SaaS/Product Sites
Product pages lack content depth
Blog not integrated with product pages
Missing comparison/alternative pages
Feature pages thin on content
No glossary/educational content
E-commerce
Thin category pages
Duplicate product descriptions
Missing product schema
Faceted navigation creating duplicates
Out-of-stock pages mishandled
Content/Blog Sites
Outdated content not refreshed
Keyword cannibalization
No topical clustering
Poor internal linking
Missing author pages
Multilingual / Multi-Regional Sites
Hreflang errors (missing return tags, invalid codes, no self-reference)
Canonical conflicting with hreflang (cross-locale canonical suppresses indexing)
Thin locale pages dragging down site-wide quality signal
Only boilerplate translated, main content identical across locales
No x-default fallback declared
Sitemap missing hreflang alternates or missing reciprocal entries
IP-based redirects hiding content from Googlebot
Framework locale mode hiding locale from URLs
Local Business
Inconsistent NAP
Missing local schema
No Google Business Profile optimization
Missing location pages
No local content
Output Format
Audit Report Structure
Executive Summary
Overall health assessment
Top 3-5 priority issues
Quick wins identified
Technical SEO Findings
For each issue:
Issue: What's wrong
Impact: SEO impact (High/Medium/Low)
Evidence: How you found it
Fix: Specific recommendation
Priority: 1-5 or High/Medium/Low
On-Page SEO Findings
Same format as above
Content Findings
Same format as above
Prioritized Action Plan
Critical fixes (blocking indexation/ranking)
High-impact improvements
Quick wins (easy, immediate benefit)
Long-term recommendations
References
AI Writing Detection: Common AI writing patterns to avoid (em dashes, overused phrases, filler words)
International SEO: Evidence and sources for hreflang, canonical + i18n, sitemaps, URL structure, and content quality across locales
GEO: Evidence and sources for generative-engine visibility — the KDD 2024 measurement of what works, passage-level extraction, freshness, structured-data correlation, the AI-crawler agent table (training vs retrieval), and why llms.txt is not a visibility tactic
Tools Referenced
Free Tools
Google Search Console (essential)
Google PageSpeed Insights
Bing Webmaster Tools
Rich Results Test (use this for schema validation — it renders JavaScript)
Mobile-Friendly Test
Schema Validator
Note on schema detection:web_fetch strips <script> tags (including JSON-LD) and cannot detect JS-injected schema. Use the browser tool, Rich Results Test, or Screaming Frog instead — they render JavaScript and capture dynamically-injected markup. See the Schema Markup Detection Limitation section above.
Paid Tools (if available)
Screaming Frog
Ahrefs / Semrush
Sitebulb
ContentKing
Task-Specific Questions
What pages/keywords matter most?
Do you have Search Console access?
Any recent changes or migrations?
Who are your top organic competitors?
What's your current organic traffic baseline?
AKILI-SPECS Integration
AKILI moment
How to use this skill
/akili-seo audit phase
Required skill — load before starting and apply throughout; the Audit Report Structure above is the finding format
/akili-validate
When validating pages with search-visibility requirements, apply the On-Page checklist to the affected routes
Adaptation rules:
Findings land in the AKILI report artifacts (/akili-seo output), using the Issue / Impact / Evidence / Fix / Priority shape.
Fixes that exceed the trivial gate are routed through /akili-propose — never applied silently during the audit.
GEO findings use the same Issue / Impact / Evidence / Fix / Priority shape. Label the source tier when citing a magnitude: the KDD 2024 figures are peer-reviewed, the AI Overview and crawler-behaviour figures are industry analyses. Never present an [INDUSTRY] number to a client as measured fact.
Sibling skills mentioned by upstream versions of this skill (programmatic-seo, cro, analytics) are not packaged with AKILI-SPECS; when a finding needs them, note the gap in the report instead of loading them. The upstream schema and ai-seo gaps are now covered in-skill by the Structured Data and GEO sections.
