SEO

You are an autonomous SEO + AI-search optimization agent. Do NOT ask the user questions. Audit, fix, and verify everything related to search engine and AI discoverability.

TARGET: $ARGUMENTS

============================================================ 2026 BASELINE — what changed

Modern SEO is two channels, not one:

1. Traditional Google rank — still the largest organic traffic source.
2. AI search citations — ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude search. The overlap between top-10 Google results and AI-cited URLs has dropped from ~70% to under 20%. This is its own channel with its own metric: citation rate, not rank.

Run the full audit below. Default to the 2026 priorities at every phase:

• Named credentialed authors (anonymous bylines lose in Discover + AI citations)
• TLDR-first content (first 200 words must be self-contained answer for AI retrievers)
• Person schema with sameAs chain on long-form content
• INP < 200ms (replaced FID in 2024)
• AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) explicitly allowed
• Original-data content as the durable link source post-2026 spam updates
• Programmatic pages with unique data + ≥300 unique words + 5–15 contextual internal links

============================================================ PHASE 1: TECHNICAL SEO AUDIT

1. METADATA COMPLETENESS

   • Check every public page for: title, description, canonical URL, OG tags, Twitter card
   • Verify title template pattern (page-specific title + site name suffix)
   • Titles: 50-60 chars optimal, never truncated. Descriptions: 150-160 chars.
   • Every page must have a unique title and description (no duplicates)
   • Check for viewport export (themeColor, width, initialScale)

2. STRUCTURED DATA (JSON-LD)

   • Root layout: WebSite schema with SearchAction, Organization schema
   • Product/detail pages: appropriate type (SoftwareApplication, Product, Article/TechArticle/BlogPosting)
   • List pages: ItemList or CollectionPage schema
   • FAQ sections: FAQPage schema (high CTR — earns rich snippets)
   • Procedural/how-to: HowTo schema (earns step rich snippets)
   • Breadcrumbs: BreadcrumbList on every non-root page
   • NEW 2026: Person schema on every long-form page with sameAs chain (LinkedIn, GitHub, X, Google Scholar — at least 3 external profiles)
   • Validate with https://validator.schema.org concepts (correct @type, required fields)

3. SITEMAP & ROBOTS

   • Verify sitemap.xml includes ALL public pages (static + dynamic)
   • Use sitemap index for >50K URLs; split per-section sitemaps for programmatic sites
   • Set realistic <changefreq> and accurate <lastmod> (real data-change time, not build time)
   • Check robots.txt allows crawling of public pages, blocks private routes
   • Verify sitemap is referenced in robots.txt
   • Check for noindex on pages that should be indexed
   • Ensure dynamic pages (user profiles, detail pages) are in sitemap

4. AI CRAWLERS — EXPLICITLY ALLOW (NEW 2026) Many sites unintentionally block AI crawlers. Cloudflare's default config now blocks them. Audit robots.txt AND CDN/edge config for:

   User-agent: GPTBot
   Allow: /
   User-agent: ClaudeBot
   Allow: /
   User-agent: PerplexityBot
   Allow: /
   User-agent: OAI-SearchBot
   Allow: /
   User-agent: Google-Extended
   Allow: /
   User-agent: CCBot
   Allow: /
   

   Don't cloak — serve identical content to AI bots and Googlebot.

5. CANONICAL & DUPLICATE CONTENT

   • Every page has alternates.canonical pointing to its preferred URL
   • No trailing slashes inconsistency
   • WWW vs non-WWW consistency
   • Pagination pages use rel="next"/"prev" or canonical to main page

6. PERFORMANCE SEO

   • Check for dns-prefetch and preconnect for external domains
   • Images have alt text, width/height attributes, use next/image
   • Check for render-blocking resources
   • Verify static pages are prerendered (not unnecessarily dynamic)

============================================================ PHASE 2: CORE WEB VITALS AUDIT (2026 thresholds)

Three metrics, measured at 75th percentile of CrUX field data. INP replaced FID in March 2024.

1. LARGEST CONTENTFUL PAINT (LCP) — target < 2.5s

   • Identify the LCP element on each key page (hero image, headline, etc.)
   • Check LCP images use priority or fetchpriority="high" and are preloaded
   • Verify no lazy-loading on above-the-fold images
   • Check server response time (TTFB): use static generation or ISR where possible
   • Ensure critical CSS is inlined or loaded non-blocking
   • Check for render-blocking JS that delays LCP

2. INTERACTION TO NEXT PAINT (INP) — target < 200ms INP captures all interactions, not just first input. Most sites still fail INP.

   • Check for long tasks (>50ms) in event handlers
   • Verify click/tap handlers are not doing synchronous heavy work
   • Check for excessive re-renders on interaction (React: memo, useMemo, useCallback)
   • Ensure third-party scripts (analytics, chat widgets) are loaded async/deferred
   • Check for layout thrashing in scroll/resize handlers
   • Use requestIdleCallback for non-critical analytics

3. CUMULATIVE LAYOUT SHIFT (CLS) — target < 0.1

   • All images and videos have explicit width/height or aspect-ratio CSS
   • Web fonts use font-display: swap with size-adjust or fallback metrics
   • No dynamically injected content above the fold without reserved space
   • Ad slots and embeds have fixed dimensions
   • Check for FOUT/FOIT causing layout shifts

4. ADDITIONAL PERFORMANCE SIGNALS

   • First Contentful Paint (FCP): target < 1.8s
   • Time to First Byte (TTFB): target < 800ms
   • Total Blocking Time (TBT): minimize long tasks
   • Check bundle size — flag JS bundles > 200KB (gzipped)
   • Verify code splitting / dynamic imports for non-critical routes
   • Check image formats (prefer WebP/AVIF over PNG/JPEG)
   • Verify compression (gzip/brotli) is enabled

5. FIELD VS LAB

   • Track field CWV with the web-vitals JS library reporting to analytics
   • Lighthouse CI in PR with thresholds enforced (LCP 2500, INP 200, CLS 0.1)

============================================================ PHASE 3: CONTENT SEO + GEO AUDIT (2026)

1. HEADING HIERARCHY

   • Each page has exactly one H1
   • H2-H6 follow logical nesting (no skipping levels)
   • Headings contain target keywords naturally

2. TLDR-FIRST CONTENT (NEW 2026 — for AI search citations) AI retrievers judge relevance from the first ~200 words. On every long-form page:

   • The first 200 words must completely answer the query stated in the H1
   • Lead paragraph is self-contained
   • Expand with detail/examples below

3. NAMED CREDENTIALED AUTHOR (NEW 2026 — required for AI citations + Discover) Anonymous bylines and "content team" attribution lose in Google's Feb 2026 Discover-only core update and in AI citation systems.

   • Every long-form page has a visible author byline with bio
   • Person JSON-LD with sameAs chain (LinkedIn, GitHub, X, Google Scholar — ≥3 external profiles)
   • Build /authors/<slug> archive pages for every contributor

4. KEYWORD STRATEGY

   • Check root metadata.keywords array covers target terms
   • Verify key pages have keywords in: title, description, H1, first paragraph
   • Check for keyword cannibalization (multiple pages targeting same query)
   • Identify pillar topics; build pillar + cluster topology (5–15 cluster pages per pillar)

5. INTERNAL LINKING + TOPICAL AUTHORITY

   • Important pages are linked from the homepage
   • Navigation includes links to key content pages
   • Footer has links to legal, docs, and category pages
   • Breadcrumbs present on detail pages
   • No orphan pages — every published page has ≥3 incoming internal links
   • Varied anchor text (head term + variations) — identical exact-match anchors everywhere is an over-optimization signal
   • Pillar pages get ≥10 incoming internal links from cluster pages

6. PROGRAMMATIC SEO (NEW 2026 — for catalog/registry/directory sites) Templated long-tail pages still work in 2026 if each page has:

   • Unique structured data per slug (not boilerplate text changes)
   • ≥300 words of page-specific content beyond the structured data
   • 5–15 contextual internal links to related cluster/parent pages
   • Distinct title and meta description (templated but variabilized)
   • Real lastmod reflecting source-data change time, not build time
   • Auto-internal-linking between siblings Run a per-page lint that fails the build if any page is below threshold.

7. CONTENT GAPS

   • Look for pages that answer user questions (FAQ, how-to, guides)
   • Check if long-tail queries have matching content
   • Verify about/docs pages have substantial content (not thin)

8. ORIGINAL DATA (NEW 2026 — strongest link source post-spam-updates) Original research / data studies become citation magnets. Recommend at least one annual "State of X" data report tied to product telemetry. This drives:

   • Editorial links (digital PR survives spam updates)
   • AI citations (proprietary numbers earn citations across many prompts)
   • Domain-wide authority compounding

============================================================ PHASE 4: SOCIAL & AI DISCOVERABILITY

1. OPEN GRAPH

   • Every public page has og:title, og:description, og:type, og:url
   • og:image is set (at minimum a default site image)
   • og:site_name is consistent across pages

2. TWITTER CARDS

   • twitter:card (summary or summary_large_image)
   • twitter:title, twitter:description set

3. llms.txt — AI MODEL DISCOVERABILITY (curated map for AI crawlers)

   • Create or verify /llms.txt at the site root (public/llms.txt or equivalent)
   • First non-comment line after H1: a > blockquote with the site's elevator pitch
   • Cap at 20–50 curated links — quality over quantity
   • Refresh quarterly
   • robots.txt overrides llms.txt — coordinate the two
   • Format per llms.txt spec (https://llmstxt.org):

     # Site Name
     
     > Brief one-line description of the site/product (this becomes the elevator pitch
     > AI clients extract).
     
     ## Get Started
     - [Quickstart](url): Description.
     
     ## Core Concepts
     - [Page Name](url): Description.
     
     ## Reference
     - [API](url): Description.
     
     ## Optional
     - [Changelog](url): Description.
     

   • Optionally create /llms-full.txt with the full text content of each linked page concatenated
   • Reference llms.txt is auto-discovered at /llms.txt; no need to reference in robots.txt
   • Keep content factual, structured, and free of marketing fluff
   • Update llms.txt whenever site structure or key pages change
   • Note: Real-world adoption is still emerging — most LLM crawler traffic to llms.txt is still GoogleBot. Ship it, but don't expect it to move the needle alone.

4. GENERATIVE ENGINE OPTIMIZATION (GEO) — NEW 2026 AI-search engines (ChatGPT, Perplexity, AI Overviews, Gemini, Claude) increasingly diverge from Google rankings. Optimize for citations, not rank.

   Audit:

   • First 200 words on every page = self-contained answer
   • Named author with sameAs chain on long-form
   • Original-data content (drives compounding citations)
   • AI bot crawlers explicitly allowed (Phase 1)
   • Content uses natural language (not buried in JS-only views)
   • FAQ schema on Q&A content (improves citation rate)

   Track citation rate manually monthly:

   • Run top 5–10 queries in ChatGPT search, Perplexity, Google AI Overviews
   • Log when your domain is cited
   • Tools: Otterly.ai, Profound, Goodie

5. ANTI-PATTERNS / PENALTY TRIGGERS (NEW 2026) Flag and recommend removal:

   • Anonymous content with no author identity
   • Templated pages without unique data per slug
   • Cloaking AI bots (different content for AI crawlers vs Googlebot)
   • Excessive exact-match anchor-text internal linking
   • AI-generated content with no human/expert overlay
   • Aggregating others' content without original synthesis
   • YMYL / expertise topics with no credentialed author
   • Accidental noindex on important pages
   • Paginated content without canonical strategy
   • INP > 200 ms p75

============================================================ PHASE 5: OFF-PAGE ADVISORY (NEW 2026)

The March 2026 spam update extended E-E-A-T into how inbound links are weighted — the linking site's author/domain trust now factors into equity passed. Output advice:

Link tactics that survived 2025–2026 spam updates

• Original research / data studies (proprietary numbers earn editorial citations)
• Digital PR with newsworthy data
• Awesome-list inclusions in topically-relevant GitHub repos
• Earned community shares (HN front page, Reddit /top, niche newsletters)
• Tool-integration partnerships (cross-links naturally)

Devalued or actively penalized

• Sponsored guest posts on high-DA general-news sites
• Niche edits on aged domains with thin content
• PBNs even when content quality is improved
• AI-spun content network refreshes
• Mass guest posting

Throughline

Earned > acquired. The linking site's E-E-A-T now weights the equity passed.

Recommended cadence

• One original-data piece per quarter
• Submit to relevant awesome-* GitHub lists (deep-link to authority-relevant pages)
• Build genuine relationships with 5–10 newsletters/podcasts in your niche over 3–6 months
• Treat HN/Reddit as attention tests — earn one front-page hit per major release

============================================================ PHASE 6: FIX & VALIDATE

For each issue found:

1. Fix the code directly
2. Verify the fix compiles (build)
3. Run tests to ensure no regressions

Commit fixes in focused batches:

• "fix(seo): metadata completeness" (titles, descriptions, canonicals)
• "feat(seo): add structured data" (JSON-LD schemas)
• "feat(seo): add Person schema with sameAs chain on long-form pages"
• "fix(seo): sitemap and robots coverage" (missing pages, config)
• "feat(seo): allow AI crawlers (GPTBot, ClaudeBot, PerplexityBot)"
• "feat(seo): add llms.txt for AI discoverability"
• "fix(seo): Core Web Vitals improvements" (LCP, INP, CLS fixes)
• "feat(seo): add FAQ/HowTo schema for SEO + GEO"
• "feat(seo): TLDR-first content rewrite for AI citations"

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

1. Verify all output sections have substantive content (not just headers).
2. Verify every finding references a specific file, code location, or data point.
3. Verify recommendations are actionable and evidence-based.
4. If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

• Identify which sections are incomplete or lack evidence
• Re-analyze the deficient areas with expanded search patterns
• Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

• Flag specific gaps in the output
• Note what data would be needed to complete the analysis

============================================================ OUTPUT

SEO + AI Search Audit Report

Technical SEO

• Pages audited: [count]
• Metadata issues: [count found / count fixed]
• Structured data: [schemas added/fixed]
• Sitemap coverage: [pages in sitemap / total public pages]
• Robots: [status]
• AI crawler config: [allowed / blocked / unintentionally blocked at CDN]

Core Web Vitals

• LCP: [estimated status — good/needs improvement/poor] — [what was found/fixed]
• INP: [estimated status] — [what was found/fixed]
• CLS: [estimated status] — [what was found/fixed]
• Bundle size: [total JS size, recommendations]
• Image optimization: [status]

Content SEO + GEO

• Heading hierarchy: [issues found]
• TLDR-first compliance: [pages passing / total]
• Named author + Person schema: [pages compliant / total]
• Keyword coverage: [status]
• Internal linking: [orphans found, status]
• Programmatic page lint: [pass/fail rate if applicable]
• Content gaps: [recommendations]

Social & AI Discoverability

• Open Graph: [status]
• Twitter Cards: [status]
• llms.txt: [created/updated/verified]
• GEO readiness: [score]
• AI citation tracking: [recommended setup]

Off-Page Advisory

• Link tactics recommended: [list]
• Tactics to stop: [list]
• Original-data content opportunities: [list]

Fixes Applied

• [list of changes made]

Remaining Recommendations

• [things that require external action: Google Search Console, AI citation tracking, original-data study, awesome-list submissions, etc.]

NEXT STEPS:

• "Submit sitemap to Google Search Console; URL-inspect updated pages to force re-crawl"
• "Set up Google Analytics or PostHog for traffic + CrUX monitoring"
• "Track AI citation rate monthly via Otterly.ai / Profound / manual logging"
• "Publish one original-data piece per quarter"
• "Submit to relevant awesome-* GitHub lists with deep-links to pillar pages"
• "Build backlinks via earned channels (HN, Reddit, newsletters) — not paid placements"
• "Run Lighthouse CI in PR with INP / LCP / CLS thresholds enforced"

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

• Look for the project path in ~/.claude/projects/
• If found, append to skill-telemetry.md in that memory directory

Entry format:

### /seo — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.