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seo-eeat

seo-eeat

github.com/hainrixzMarketing & growth79204 installsUpdated 4d ago
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About seo-eeat

An SEO skill that reviews visible expertise, author identity, organizational trust, and transparency signals on a page. It helps teams assess what readers and AI systems can verify, without treating these signals as a direct ranking score.

Key features

  1. 01Review author identity and credentials
  2. 02Check organization and contact signals
  3. 03Assess first-hand expertise evidence
  4. 04Inspect sourcing and disclosures
  5. 05Validate trust-related JSON-LD

Use cases

  1. 01Review author and organization information
  2. 02Find missing disclosures on sponsored content
  3. 03Check whether expertise claims have visible evidence

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hainrixz/claude-seo-ai --skill seo-eeat

After installing, type/seo-eeatin Claude Code to confirm it loaded.

Details

From the project README

seo-eeat (M16)

Experience, Expertise, Authoritativeness, and Trust are how both Google's quality systems and AI answer engines decide whether to rely on a page. Trust is foundational and now applies beyond YMYL. Schema details: references/schema-tier1.md.

Inputs

Work from the PageSnapshot named in your dispatch envelope: read parsed from <run_dir>/pages/<slug>.json (jsonld[], anchors[], text_sample); Grep pages/<slug>.html for verbatim evidence; site artifacts live in <run_dir>/site/{robots.json,sitemaps.json,discovery.json}. Deterministic findings already emitted by audit.mjs are listed in <run_dir>/findings.deterministic.json — do not re-emit those ids; add model-judged findings only. If invoked directly with a URL/path and no snapshot exists, first run node "${CLAUDE_PLUGIN_ROOT}/scripts/snapshot.mjs" <target> --out "${CLAUDE_PLUGIN_DATA}/runs" and use the printed snapshot path.

Audits

Working from the PageSnapshot (parsed_rendered when render.used is not none, else parsed):

  1. Author identity & credentials: is there a visible byline? A Person schema with name, jobTitle, knowsAbout, and sameAs[] (LinkedIn/Wikidata)? Does the byline link to an author/bio page? Are credentials/experience stated, not just a name?
  2. Organization trust: discoverable About and Contact pages; an Organization block with name, url, logo, contactPoint, sameAs[]; visible editorial/privacy/returns policies appropriate to the vertical.
  3. Experience & expertise markers: first-hand signals (original photos, "we tested", dates, methodology) and topical depth — not just generic prose.
  4. Transparency: sourcing/citations for claims, author disclosures (affiliate, sponsored, AI-assisted), last-reviewed dates. Defer the sameAs identity-graph detail to M6/seo-entity-linking.

Fixes

  • AUTO (fixable: auto): inject Person (author) and Organization trust JSON-LD built only from confirmed inputs — name, jobTitle, contactPoint, policy URLs the user supplies. The block is a diff for fix.
  • PROPOSED (fixable: proposed): draft a byline link or a sameAs set for per-item accept.
  • ADVISORY (fixable: advisory): writing real author bios, About/contact pages, or editorial policies — the tool never authors these. Never fabricate names, credentials, dates, or identity links — ask the user or leave a clearly-marked TODO placeholder.

Verification

  • Offline: node "${CLAUDE_PLUGIN_ROOT}/scripts/validate-jsonld.mjs" --snapshot <pages/<slug>.json> (or --url <u>) plus dom_assert for visible byline/links/policy pages.
  • When confirming an identity link or a live About/contact page requires a fetch that is unavailable, status is needs_api — never a false pass.

Findings

Emit findings per schema/finding.schema.json; axis both. Severity policy: 5 is reserved for catastrophic, eligibility-killing facts at site/template scope; 4 major · 3 moderate · 2 minor · 1 cosmetic · 0 informational — and only an established severity-5 fail in an active category can cap a score (references/scoring-model.md). Examples:

  • M16.author.missing_person_schema — an editorial page with a byline but no Person schema (fail, severity 3, fixable: auto, confidence established — the markup requirement is documented; the ranking effect is not, and belongs in rationale as directional).
  • M16.author.no_bio_page — the byline does not link to an author/bio page (warn, severity 3, fixable: proposed, confidence directional).
  • M16.org.no_contact_page — no discoverable About/Contact and no contactPoint (warn, severity 3, fixable: advisory, confidence directional).
  • M16.transparency.no_disclosure — affiliate, sponsored, or AI-assisted content with no visible disclosure (warn, severity 3, fixable: advisory, confidence directional). Each finding: evidence.observed quotes what is on the page; verification.reproduce is the runnable command above; expected_impact is banded + confidence-tagged (no naked %).

Honesty

  • E-E-A-T is not a score Google exposes, and Google's own framing is "people-first content". Its guidance asks who, how, and why: is there a real author with real experience, was the content made for readers rather than for engines. Everything this module measures is a visible proxy for that judgment, so every finding here is directional — adding a Person block or an author bio is not a ranking lever, and must never be presented as one.
  • Trust is the foundational element and now applies well beyond YMYL, but a page does not become trustworthy by acquiring markup. Report missing signals as "a reader (or an AI system) cannot tell who stands behind this", not as points lost.
  • A fabricated author, an invented credential, or fake review markup is worse than nothing — it is a trust risk in Search and in AI answers alike. The tool only emits trust signals the user can substantiate, and leaves a clearly-marked TODO where it cannot.

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