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Seo freshness

Skill Hainrixz/claude-seo-ai/skills/seo-freshness

Audit and repair freshness & temporal signals on a page — reconcile visible publish/update dates with schema datePublished/dateModified, flag staleness against topic volatility, and inject honest dateModified. Module M13. Feeds both the Search SEO and AI Visibility scores.From its SKILL.md

Install
npx -y skills add Hainrixz/claude-seo-ai --skill seo-freshness

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SKILL.md

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seo-freshness (M13)

Freshness is a recency signal both classic ranking systems (Query Deserves Freshness) and AI answer engines weigh — Perplexity in particular favours recently-updated sources when citing. Date fields tie directly to Article schema (cross-check M5); see references/schema-tier1.md for the date rules.

Audits

Working from the PageSnapshot (rendered_dom if present, else raw_html):

  1. Visible dates: detect on-page "Published" / "Updated on" / "Last reviewed" patterns and their values (ISO or human-readable).
  2. Schema dates: parse datePublished/dateModified from JSON-LD Article/BlogPosting/NewsArticle.
  3. Agreement: visible date and schema date must match; flag mismatches and schema dates with no visible counterpart (AI engines distrust hidden-only dates).
  4. Staleness: estimate content age (most recent reliable date) vs topic volatility — fast-moving topics (prices, tooling, "best X 2026", regulations) decay faster than evergreen reference content. Report stale, not just old.
  5. Pattern hygiene: "updated on" with no substantive content change is a freshness anti-pattern — note it, never recommend it.

Fixes

  • AUTO (fixable: auto): inject a missing dateModified into existing Article schema as an additive diff for fix. Never backdate to a false date — use the verifiable last-change date (e.g. Last-Modified header / repo mtime / today) or leave a clearly-marked TODO placeholder the user confirms.
  • PROPOSED (fixable: proposed): surface visible-vs-schema date mismatches with the corrected value as a draft requiring per-item accept; never auto-rewrite a date the user must verify.
  • ADVISORY (fixable: advisory): recommend a genuine content refresh for stale-on-volatile pages — the tool never writes editorial content. Never fabricate dates or invent an update that did not happen.

Verification

  • dom_assert: visible date string present and parses; matches schema value.
  • schema_validator: datePublished/dateModified present, valid ISO 8601, dateModified >= datePublished.
  • header_check: HTTP Last-Modified header corroborates the claimed modification date.
  • When the live tier (header fetch / validator) is unavailable, status is needs_api, never a false pass.

Findings

Findings conform to schema/finding.schema.json. Examples:

  • M13.datemodified.missing — Article schema with datePublished but no dateModified (status fail, severity 3, fixable: auto, axis both, confidence directional).
  • M13.dates.visible_schema_mismatch — visible "Updated May 2025" vs schema dateModified: 2023-01-10 (status warn, severity 3, fixable: proposed, axis both, confidence directional).
  • M13.content.stale_volatile — "best X 2024" page unchanged for 2 years on a fast-moving topic (status warn, severity 2, fixable: advisory, axis both, confidence directional). Each finding: evidence.observed quotes the page (date string + selector); verification.reproduce is a runnable assertion (e.g. node scripts/check-freshness.mjs --url <u>); expected_impact is banded + confidence-tagged, with any published number confined to rationale with a citation.

Honesty

  • Freshness is a contextual signal, not a universal ranking boost — refreshing evergreen content rarely moves rankings, and a dateModified bump without a real content change is detectable and adds no durable value. Confidence here is directional, never established; never present a date edit as a guaranteed ranking gain or backdate to fake recency.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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Said here and by no other author read

  • detect on-page publish or update date patterns
  • parse datePublished and dateModified from schema
  • flag mismatches between visible and schema dates
  • estimate content staleness against topic volatility
  • inject a missing dateModified into schema automatically
  • surface visible-versus-schema mismatches as a proposed fix

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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