/seo-content-audit

name: seo-content-audit
description: E-E-A-T + CITE quality audit for an EXISTING piece of content. Scores Experience, Expertise, Authoritativeness, Trustworthiness, and citation-readiness for AI search; surfaces veto items that block publication; produces a publish / publish-with-fixes / no-publish verdict. Distinct from `seo-content-brief` (produces a NEW article from a topic) and from `seo-page` (URL-level keyword/traffic intelligence). Use when the user asks "content quality audit", "E-E-A-T check", "is this content good", "review this article", "content audit", "citation readiness", or "AI search readiness".

> Example output: [examples/seo-content-audit-stripe-rate-limiters-20260514/VERDICT.md](../../examples/seo-content-audit-stripe-rate-limiters-20260514/VERDICT.md)

Content Quality Audit

Score an existing piece of content against modern E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) and CITE (Clear answer, Include primary stats, Timestamp, Entity authority) rubrics. Surface veto items that block publication regardless of overall score. Produce a clear publish / publish-with-fixes / no-publish verdict with the top 5 fixes.

Prerequisites

• SE Ranking MCP server connected.
• Claude's `WebFetch` tool available.
• User provides: (a) the URL of an existing piece of content (or pasted content + intended URL), (b) target keyword the content is meant to rank for. Optional: target country (default `us`).

Process

1. **Fetch content** `WebFetch` (always) + `mcp__firecrawl-mcp__firecrawl_scrape` (when available)

• **Validate target & preflight.** See `skills/seo-firecrawl/references/preflight.md` for the canonical 3-stage preflight (credit balance, Firecrawl availability, Google APIs). Skill-specific notes:
• Estimated SE Ranking cost for this skill: ~10–15 credits typical (AIO context + AIO prompt sampling for the target keyword + audited URL).
• Firecrawl: optional with WebFetch fallback, 1 Firecrawl credit per URL audited (default cap 50 URLs, hard cap 200). Surface the projected Firecrawl credit count before continuing. Pass `--no-firecrawl` to force WebFetch-only inspection (lower-confidence veto checks; see step 4 caveat).
• Google APIs: tier 2 (GA4 available) unlocks step 3b (GA4 organic traffic on the audited URL) after the AIO context step. See `skills/seo-google/references/cross-skill-integration.md` § "seo-content-audit" for the full recipe.
• **WebFetch first** (free, instant): pull the markdown for word count, H-tag hierarchy, source citations (links to authorities, numbered references), images, tables, code blocks, comment thread.
• **Page-type detection.** From the URL pattern, H1 phrasing, and JSON-LD `@type`, classify the page as one of: ultimate guide / pillar, how-to, listicle / best-of, comparison (X vs Y), explainer, review (single product), landing page (commercial). Look up the corresponding word-count floor from `references/core-eeat.md` → "Word-count floors by page type". Surface the detected type, the applied floor, and the actual word count in `evidence/01-content-snapshot.md`. If the actual word count is materially below the floor, flag it for the depth E-E-A-T items (auto ✗ unless the auditor justifies the exception).
• **Firecrawl second** — recovers what WebFetch's markdown loses:
• From `metadata`: canonical URL, robots, lang, `og:title`.
• From the returned `html`: every `<script type="application/ld+json">` block. Parse for `Article` / `BlogPosting` schema and extract `author` (name, `@type: Person`, optional `url` + `sameAs`), `datePublished` / `dateModified` (ISO 8601), `publisher`, `mainEntityOfPage`. Detect `Person` schema standalone if present.
• DOM-level byline detection: locate the structural byline (`<a rel="author">`, `<meta name="author">`, `<span class="byline">`, `[itemprop="author"]`). Distinguish a real byline element from prose mentions ("Written by Jane in collaboration..." in body text is not a byline; `<a rel="author">Jane Doe</a>` is).
• **If Firecrawl unavailable:** WebFetch portion runs unchanged. Mark schema-type detection and structural byline detection as `(skipped — Firecrawl required)` in `evidence/01-content-snapshot.md`. Step 4's veto checks #1 and #4 fall back to prose-level inspection (less reliable) — surface that caveat in `VERDICT.md`.

2. **AIO context** `DATA_getAiOverview` and `DATA_getAiOverviewLeaderboard`

• For the target keyword: is there an AIO?
• Who is cited in the AIO?
• Is the candidate URL cited?
• What patterns characterise the cited sources (publication tier, freshness, structure)?

3. **AIO prompt sampling** `DATA_getAiPromptsByTarget`

• Sample LLM prompts where the target URL's domain appears as a source.
• Cross-reference with the candidate URL — does it show up in any sampled prompts?

3b. **GA4 organic traffic on the audited URL** *(only if google-api.json is present, tier ≥ 2)*

• Replaces the implicit traffic estimation with actual measured organic sessions for the audited URL.
• Pull the top organic landing pages (last 28 days):

`python3 scripts/ga4_report.py --report top-pages --days 28 --json`

• Filter the result client-side for the audited URL's path. Surface in `VERDICT.md` "## Snapshot" alongside the existing AIO citation cross-check:
• GA4 organic last 28d: `{sessions} sessions / {users} users / avg engagement {n}s`
• If the URL doesn't appear in the top-100 organic landing pages: "GA4: not in top-100 organic landing pages last 28d — low or zero traffic."
• **This is a signal, not a veto.** Low GA4 traffic on a YMYL page with high E-E-A-T is informative ("we're not earning the visibility our content quality should support") but doesn't change the publish decision.
• See `skills/seo-google/references/cross-skill-integration.md` § "seo-content-audit" for the full recipe.

4. **Score E-E-A-T** using `references/core-eeat.md`

• 60-item rubric across 4 dimensions (15