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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.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | seo-freshness |
| description | 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. |
| allowed-tools | Read, Grep, Glob, WebFetch, Bash |
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.
Working from the PageSnapshot (rendered_dom if present, else raw_html):
datePublished/dateModified from JSON-LD Article/BlogPosting/NewsArticle.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.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.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.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.needs_api, never a false pass.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.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.Audit a website or web codebase for SEO and AI-search (GEO/AEO) — produces two independent 0-100 scores (Search SEO + AI Visibility) plus a prioritized, evidence-backed report. Read-only; never writes files. Use when the user asks to audit, analyze, check, or score a site's SEO, structured data/schema, meta tags, Core Web Vitals, robots.txt, sitemaps, or llms.txt, or how it ranks in Google and is cited by AI engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude).
Opt-in fixer (the /claude-seo-ai:fix command). Applies the safe, deterministic SEO/AI-search fixes from an audit to the user's code — meta viewport/charset/lang, JSON-LD, robots.txt AI directives, hreflang, sitemaps, OG/Twitter cards, image dimensions, canonical, llms.txt. Dry-run preview by default; writes only after explicit per-change confirmation. Runs only when the user invokes it — never auto-triggered.
Analyze and score only a page's AI-search visibility (GEO/AEO) — answer extractability, fact density, AI-crawler access, entity linking, and llms.txt — and report an AI Visibility score with a citability breakdown. Read-only. Use for "will AI engines cite this?", GEO/AEO, or ChatGPT/Perplexity/Google AI Overviews/Gemini optimization.
Recompute and display the two scores (Search SEO + AI Visibility) from the most recent audit's findings, without re-crawling. Use to re-show or refresh the scores after an audit, or to score a saved findings JSON file.
Audit AI crawler access and citability for a page — confirm retrieval/citation bots (OAI-SearchBot, Claude-SearchBot, PerplexityBot) are allowed and the Googlebot vs Google-Extended split is correct, classify training vs search/retrieval vs user-fetch user-agents, check the page is server-rendered enough for non-JS AI crawlers, validate llms.txt / llms-full.txt (also covers M21), and generate a choice-gated robots.txt preset. Module M14. Feeds the AI Visibility score.
Audit Core Web Vitals & page performance — measure LCP, INP, and CLS against p75 field thresholds, diagnose render-blocking resources, unoptimized images, and layout-shift sources, and produce prioritized, advisory-only remediation guidance. Module M15. Feeds the Search SEO score (heavily) and the AI Visibility score (minimally).