SEO Content

Content Quality, E-E-A-T & Content Briefs

Two modes:

1. Audit an existing page — score quality, E-E-A-T, citability; emit ranked, falsifiable fixes.
2. Brief — produce a competitive content brief / outline a writer can ship.

This skill is for the content layer. For rendering meta tags, JSON-LD, and feeds in Next.js, cross-reference seo-technical; for AI-search surfaces, seo-geo.

Google's "Who / How / Why" test (run this first)

Before scoring sub-factors, every page must pass Google's own three-question helpful-content heuristic. This is the cheapest, highest-signal check.

Primary source: https://developers.google.com/search/docs/fundamentals/creating-helpful-content

When all three answers are weak, the page is at risk under the core ranking system's helpfulness signals (formerly the standalone Helpful Content System, merged into core during the March 2024 core update — no longer a separate classifier; helpfulness is now weighted continuously in every core update).

E-E-A-T framework

Experience (first-hand signals)

Original research, case studies, before/after results, personal anecdotes, process documentation, proprietary data, photos/videos from direct experience.

Expertise

Author credentials and bio, professional background relevant to topic, technical depth matched to audience, accurate well-sourced claims.

Authoritativeness

External citations and backlinks from authoritative sources, brand mentions, industry recognition, citation by other experts.

Trustworthiness (weighted highest)

Contact info / physical address, privacy policy & terms, customer testimonials/reviews, date stamps, transparent corrections, HTTPS. For YMYL, Trust is the gate — a page that fails Trust cannot be rescued by the other three.

Search-intent mapping (do this before scoring or briefing)

Misjudged intent is the single most common reason good content under-performs. Classify the target query, then check the page matches.

Then ask: does the page format match the rewarded format? A long essay ranking for a transactional query, or a thin landing page for an informational query, is an intent mismatch — fix the format before tuning words.

Falsifiability: How would we know an intent fix failed? Position and CTR for the target query do not improve within 2 crawl cycles after the format change. Leading indicator: SERP feature alignment (does our page type now match the top 3 results' page type?).

Content metrics

Word count — coverage floors, NOT targets

Word count is not a direct ranking factor (Google-confirmed). These are topical-coverage floors. A 500-word page that fully answers the query beats a 2,000-word page that doesn't. Treat under-floor pages as coverage suspects, then verify by topic, not length.

Readability

Flesch Reading Ease 60–70 for general audiences; average sentence 15–20 words; paragraphs 2–4 sentences; grade level matched to audience. Readability is a quality proxy, not a ranking factor (Mueller-confirmed; Yoast deprioritized Flesch in v19.3). Use it to find walls of text, not to chase a number.

Keyword optimization

Primary keyword in title, H1, and first 100 words; natural density ~0.5–2% (above 2% review, above 3% stuffing risk); semantic variations present. First 1–2 mentions carry the most weight — diminishing returns after.

Structure

Logical heading hierarchy (one H1 → H2 → H3); scannable descriptive headings; lists/tables where they beat prose; ToC for long-form.

Linking

Internal: 3–5 relevant links per 1,000 words, descriptive anchors, no orphans. External: cite authoritative sources, reasonable count.

Originality & information gain (the helpful-content gate)

Helpfulness is now a core ranking signal, so "information gain" — what this page adds that no current result provides — is the real bar. Acceptable answers are specific:

• Proprietary data or original research
• Case studies with real outcomes
• Expert quotes / first-hand experience
• Original synthesis or a unique framework

NOT acceptable: "more detail," "better formatting," "more comprehensive." If the only gain is length, the page has no information gain.

AI-generated content markers (Sept 2025 QRG)

Google's raters formally assess whether content appears AI-generated. AI content is fine if it demonstrates genuine E-E-A-T and original value with human oversight. Flag as low-quality when you see: generic phrasing, no original insight, repetitive structure across pages, no author attribution, factual inaccuracies.

Citability & AI-citation readiness (GEO)

To be quoted by AI Overviews, AI Mode, ChatGPT, Perplexity, Copilot, surface content the way an extractor wants it:

• Quotable, self-contained statements with concrete stats/facts (a sentence that survives being copied out of context)
• Answer-first formatting — lead each section with the answer, then support it
• Strong heading hierarchy mapping questions → answers
• Tables/lists for comparative or step data
• First-party data — original numbers get cited disproportionately
• Entity clarity — brand, authors, key concepts defined and backed by Organization/Person schema (see seo-technical)
• Topical authority — clusters, not isolated pages

Per Google's own AI-optimization guidance, "AEO"/"GEO" are rebranded SEO: AI Overviews and AI Mode are grounded in the same ranking and quality systems as classic Search. Optimize fundamentals (quotability, attribution, hierarchy, freshness) rather than chasing a "separate" discipline. Note AI Mode and AI Overviews are distinct citation engines that share only a minority of cited URLs — optimize for both. Detailed workflows live in seo-geo.

Falsifiability: How would we know a citability fix failed? The page is still absent from AI-answer citations for its target questions after re-indexing. Leading indicator: does the answer-first paragraph stand alone as a coherent answer when read in isolation? If not, an extractor can't lift it.

Freshness

Publication date visible; "last updated" when revised; flag content >12 months stale for fast-moving topics. Freshness theater (date bump with no substantive change) is a why failure — do not recommend it.

Implementation: surfacing trust signals in Next.js 15

Audit findings are worthless if the stack can't render the fix. Common patterns for an App Router + Payload + next-intl site:

Author/E-E-A-T block from Payload, with Person JSON-LD:

// app/[locale]/blog/[slug]/AuthorByline.tsx  (Server Component)
import type { Author } from '@/payload-types'

export function AuthorByline({ author, updatedAt }: { author: Author; updatedAt: string }) {
  const personLd = {
    '@context': 'https://schema.org',
    '@type': 'Person',
    name: author.name,
    jobTitle: author.role,
    url: author.profileUrl,
    sameAs: author.socialLinks?.map((l) => l.url) ?? [],
  }
  return (
    <div className="flex items-center gap-3 border-t pt-4 text-sm">
      <script type="application/ld+json" dangerouslySetInnerHTML={{ __html: JSON.stringify(personLd) }} />
      {author.avatar && <img src={author.avatar.url} alt={author.name} className="h-10 w-10 rounded-full" />}
      <div>
        <p className="font-medium">{author.name}</p>
        {author.role && <p className="text-muted-foreground">{author.role}</p>}
        <p className="text-muted-foreground">
          Updated <time dateTime={updatedAt}>{new Date(updatedAt).toLocaleDateString()}</time>
        </p>
      </div>
    </div>
  )
}

Honest freshness — only show "updated" when content actually changed. Persist a contentRevisedAt in Payload that you bump on substantive edits (not on every save), and render that, never new Date():

// Render only when the body changed, not on metadata-only saves
{post.contentRevisedAt && post.contentRevisedAt !== post.publishedAt && (
  <time dateTime={post.contentRevisedAt}>Updated {fmt(post.contentRevisedAt)}</time>
)}

Article schema with author + dates belongs alongside content (full helper in seo-technical); the content layer's job is to supply real values (author, datePublished, dateModified) — never placeholder dates.

Scoring rubric (0–100)

Score each page, weighting toward Trust as Google does.

Content Quality Score = E-E-A-T (40) + Helpfulness/Info-gain (25)
                      + Structure & readability (15)
                      + Citability (10) + Freshness/intent match (10)

E-E-A-T breakdown (40 pts, Trust-weighted)

Band interpretation

Falsifiability per recommendation (mandatory)

This is the discipline that separates an audit from a wish list. Every recommendation must ship with two lines:

• Falsification: the observable that would prove the fix did not work (e.g. "if position for [query] hasn't moved within 2 crawl cycles after publishing the case study, the info-gain hypothesis was wrong").
• Leading indicator: the fast proxy you can read before rankings move (e.g. impressions in Search Console, AI-answer inclusion, SERP-feature alignment, dwell/scroll depth).

A recommendation with no falsification is an opinion. Reject your own suggestions that can't be falsified.

Audit output format

### Content Quality Score: XX/100

### Who/How/Why
- Who: pass/fail — <evidence>
- How: pass/fail — <evidence>
- Why: pass/fail — <evidence>

### E-E-A-T Breakdown
| Factor | Score | Key signals |
|--------|-------|-------------|
| Experience | XX/8 | ... |
| Expertise | XX/10 | ... |
| Authoritativeness | XX/10 | ... |
| Trustworthiness | XX/12 | ... |

### Search-intent match: <intent> — match / mismatch (why)
### Citability / AI-readiness: XX/10
### Information gain: <the specific new value, or "none — flag">

### Ranked recommendations
1. <fix> — Impact: H/M/L — Effort: H/M/L
   - Falsification: <observable that proves it failed>
   - Leading indicator: <fast proxy>

Content-brief generator (brief mode)

Produce a research-backed brief a writer can execute to outrank current results.

1. Pick the mode

• Improve (existing URL): fetch it, keep what's strong, list missing/thin/outdated sections, distinguish "keep/strengthen" vs "add new." Don't recommend a full rewrite when targeted improvements win.
• New page (keyword only): use the site's homepage/sitemap for business context, build from scratch around competitive gaps.

2. Fetch context

Read the target page (improve mode) and the sitemap — sitemap drives the Website-Relevance and internal-linking rules below. (Use your own crawler/tooling.)

3. Analyse the SERP

Identify the top ~5 ranking pages for the keyword; exclude non-competitors (Wikipedia, Reddit, Pinterest, Amazon, YouTube, gov sites, SEO-tool pages, job boards, directories, news aggregators, social). Score each real competitor: Depth /10, Formatting /10, SEO /10, UX /10. Identify three gap types:

• Topic gaps — subtopics competitors miss entirely
• Depth gaps — covered but shallow
• Quality gaps — outdated, no expert view, poor formatting

Prioritise gaps by Impact × Competitive Advantage / Effort.

4. Classify intent + rewarded format

Use the intent table above; state which SERP format Google rewards (guide / listicle / comparison / landing / FAQ / local pack).

5. Build the brief

Apply the page-type template, customise to gaps and intent.

Critical brief rules

• Website-relevance: every heading, subtopic, keyword, and FAQ must be something this site can credibly write about given its real services/products. Before each suggestion ask "can this site actually deliver this?" If no, drop it.
• Hub coverage: for hub/overview/category/"types of" pages, the outline must reference every real category/service/sub-page that exists (each as its own section + internal link) — and invent none. For spoke pages, suggest relevant internal links without forcing every category in.
• Plain output language: never name researchers, frameworks, or tools in the deliverable. Those are internal thinking tools. Write for a business owner or writer, not an SEO academic.

Keyword placement (brief)

Primary keyword MUST appear in: title (front), H1 (front), URL slug, meta description, first 100 words, ≥1 image alt. It does NOT need to be in every H2/H3 or every paragraph. Secondary: 5–8 close supporting terms + 10–15 broader semantic terms distributed naturally; synonyms aid readability and don't count toward density. Spread the primary evenly — don't cluster.

Meta-tag rules (brief)

• Title: 50–60 chars, primary keyword first, brand last (pipe or dash matching site pattern), lead with outcome/number/specific.
• Description: 130–150 chars, active voice, expand the title with USPs, end with a CTA, no brand at end, no quotes (Google truncates at them).

Brief output

## Content Brief: [Primary Keyword]

### Search Intent
[Intent, rewarded SERP format, audience + knowledge level. 3–4 lines.]

### Competitor Analysis
| # | URL | Key H2s | Est. words | Score /40 | Main gap |
|---|-----|---------|------------|-----------|----------|

### Content Gaps & Opportunities
[topic / depth / quality gaps, specific]

### Winning Outline
**H1:** [with primary keyword]
**URL slug:** /[slug]
**Target words:** ~[X] (competitor avg ~[X])
[H2/H3 outline with: words per section, format note (list/table/definition box),
 Featured-Snippet targets marked "FS target", per-section keyword guidance]

### Recommended Meta Tags
**Title** [≤60 chars]
**Meta Description** [≤150 chars]

### Unique Angle & Information Gain
[the exact new value this page adds — must be specific]

### E-E-A-T Requirements
[exact trust signals: author + credentials, expert quotes/citations, dated
 studies/stats, last-updated date; YMYL gets stricter sourcing]

### Internal Linking
[3–5 real targets from the sitemap, with anchor text; mark hub vs spoke]

Outline-only mode

When the user asks for "just an outline," drop Competitor Analysis, Gaps, Information Gain, and E-E-A-T sections; output only the H1/slug/target-words header and the full H2/H3 outline with word counts, format notes, FS targets, keyword guidance, and a 1–2 sentence writing note per section.

Error handling

Score E-E-A-T against the main-content text (boilerplate-stripped: drop nav, footers, cookie banners) so author bios and trust signals score without dilution. Never call a fetcher directly on user-supplied URLs without SSRF/DNS-rebinding protection (use your own crawler/tooling).

Parts adapted from claude-seo (MIT, © 2026 agricidaniel).