/seo-content

name: seo-content
description: Use when analyzing published content quality — E-E-A-T scoring, anti-cannibalization, keyword distribution, AI disclosure.
user-invocable: false
related-skills: seo, seo-content-brief, seo-cluster, seo-geo, seo-entity, seo-featured-snippets

<objective> Scores existing content against the E-E-A-T pillars (Experience, Expertise, Authoritativeness, Trustworthiness), runs local keyword-density analysis (`scripts/analyze-keywords.ts`) for distribution and stuffing signals (multi-signal detection — never a fixed >3% density threshold), checks anti-cannibalization (one primary keyword and intent per URL), verifies meta title/H1/heading rules and local semantic distribution, applies 2026 citation-eligible copywriting checks (answer capsule opening every H2, one hyperlinked statistic every 150-200 words, named entities instead of pronouns), and flags AI-content-disclosure requirements. Covers quality of already-written content — for planning a brief before writing, use seo-content-brief; for entity/knowledge-graph optimization, use seo-entity. </objective>

Content Quality (E-E-A-T 2026)

Content Intelligence Workflow

Before content recommendations, run `scripts/analyze-keywords.ts` (local-first, no API key). Use it as first-pass evidence for keyword distribution, semantic breadth, local modifier placement, heading coverage, and stuffing risk.

bun run scripts/analyze-keywords.ts <url-or-path> --keyword "<primary keyword>" --synonyms "<syn1,syn2>" --locations "<city1,city2>" --format markdown

It returns density, n-grams, a 0-100 stuffing score, heading coverage, and per-location contextual mentions — purely local HTML parsing.

E-E-A-T Pillars

• **Experience**: First-hand knowledge signals (case studies, photos, "I tried...")
• **Expertise**: Author credentials, depth, technical accuracy
• **Authoritativeness**: Industry recognition, citations, backlinks
• **Trustworthiness**: Contact info, HTTPS, transparent ownership, fact-checking

Anti-Cannibalization

• One primary keyword per URL
• Different search intents per page (info / navigational / transactional)
• Internal linking respects pillar/cluster topology

Metadata and Heading Rules

• Meta title must be 60 characters or less.
• Meta description must be 150 characters or less.
• Do not include the company or brand name in the meta title unless the client explicitly asks. If needed, present a branded title as an option or exception.
• Meta title and H1 should be semantically similar, but not necessarily identical.
• Meta title and H1 need the primary keyword or a strong variant.
• H2/H3 headings distribute synonyms, long-tail phrases, questions, and sub-intents.
• Avoid repeating the exact keyword across every heading.

Local Semantic Distribution

• The client's target localities (primary `[city]` + neighbouring municipalities/`[region]`) must appear naturally near service terms, never as a dumped city list.
• Prefer sentence-level relevance such as `[service]` + `[city]` + proof or context.
• On a LOCAL page, alternate `[city]` with `[region]` and district/neighbourhood names instead of repeating the same city token.

Keyword Distribution by Zone

Place terms by page zone, not by hitting a density target. Anti-stuffing 2026 is multi-signal, not a fixed percentage (Google's leaked `KeywordStuffingScore` runs 0-127; risk rises past ~3% density).

| Zone | Primary `[service]` | Local modifier `[city]/[region]` | Synonyms + entities | Secondary terms | |------|---------------------|----------------------------------|---------------------|-----------------| | Title / H1 | Yes (exact or strong variant) | Local page only | — | — | | H2 / H3 | Sparingly (1-2) | Local page only, varied | Yes (distribute) | Yes | | First 100 words / answer capsule | Yes (once) | Local page: once | Yes | — | | Body | Natural flow | Local page: spread | Yes (bulk of coverage) | Yes | | Anchors / alt / meta | Variant | Geo-specific on local | Yes | — |

Reference counts for a 1000-1500 word page:

• **Primary `[service]`**: 5-8 occurrences (~1-1.5% — the sweet spot, never above ~3%).
• **Semantic family (synonyms + named entities)**: 12-18 occurrences — this carries topical depth, not exact repetition.
• **Local modifier `[city]/[region]`**: 4-6 occurrences on a LOCAL page; 1-2 mentions on a GLOBAL page (zone signal, not stuffing). On the local page, rotate `[city]` with `[region]`/district rather than repeating one city.

Keyword Stuffing Detection

Do not use a fixed `>3%` density threshold as the stuffing rule. Flag keyword stuffing only when multiple signals align:

• Exact keyword repetition
• Repeated n-grams
• Repeated local modifiers
• Low semantic diversity
• Thin content
• Unnatural heading, anchor, or paragraph placement

`scripts/analyze-keywords.ts` computes these signals into a 0-100 stuffing score.

Copywriting 2026 (citation-eligible writing)

• **Answer capsule per H2**: open *every* H2 with a self-contained 40-60 word answer, not only the page's first 100 words. AI Overviews and LLMs extract per-section; each H2 must stand alone as a quotable verbatim answer.
• **Hyperlinked statistics**: one statistic linked to its primary source every 150-200 words. Naked or undated stats are not citation-eligible.
• **Named entities, not pronouns**: name key entities explicitly (product, person, place, organization) instead of "it", "they", "this tool". LLMs disambiguate by surface entity mentions, not coreference.
• Keep the anti-AI-slop tone: no "In conclusion...", "It's important to note...", no marketing filler.

AI Content Guidelines

• Disclose AI-assisted content where required
• Human review + first-hand experience injected
• Avoid generic AI-typical structures ("In conclusion...", "It's important to note...")

Entities and Semantics

For entity-based optimization (knowledge graph alignment, `sameAs`, entity salience, semantic depth), use the `seo-entity` skill. Anchor each