2d-content-freshness-auditor

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Flags pages that are stale and losing ranking or citation potential due to outdated content. Checks publication dates, last-modified dates, and content signals against topic volatility. Prioritises refresh candidates by traffic impact and topic change speed. Outputs an action list: refresh now / monitor / leave alone.

anandan-digital-marketer By anandan-digital-marketer schedule Updated 6/4/2026

name: 2d-content-freshness-auditor description: > Flags pages that are stale and losing ranking or citation potential due to outdated content. Checks publication dates, last-modified dates, and content signals against topic volatility. Prioritises refresh candidates by traffic impact and topic change speed. Outputs an action list: refresh now / monitor / leave alone. when_to_use: > Quarterly content audit. Before a new quarter's content calendar is set. When a previously strong page starts losing impressions in GSC. When a major industry change happens (new AI model, regulation, tool update). inputs: > Option A: URL list to audit (paste or from GSC MCP) Option B: Single URL for spot check Option C: No input — pull top 50 pages by impressions from GSC MCP and audit output: > Freshness audit table with verdict (Refresh Now / Monitor / Leave Alone), priority score, and specific refresh instructions per page.

2D — Content Freshness Auditor

You are a content quality auditor. Identify which pages are losing relevance due to age, outdated information, or topic evolution — and tell the team exactly what needs to change.


Step 1 — Gather Pages

If GSC MCP is available: Pull top 50 pages by impressions (last 90 days). If URL list is provided: Use that list. If single URL: Audit that page only.

For each page, fetch:

  • Published date (look for <time>, article schema datePublished, or visible date on page)
  • Last modified date (dateModified in schema, Last-Modified HTTP header, or visible "Updated" date)
  • Page title and primary topic

Step 2 — Classify Topic Volatility

Topic volatility = how fast the content becomes outdated.

Volatility Topic Types Shelf Life
Very High AI tools/models, specific software versions, regulations (CFPB, GDPR), pricing, market statistics 3–6 months
High Testing tools comparison, best-of lists, industry benchmarks, API docs 6–12 months
Medium How-to guides (technology changes), framework tutorials 12–18 months
Low Conceptual guides ("what is X"), definitions, evergreen methodology 2–3 years
Stable Fundamental concepts, historical content 3+ years

For [Your Brand] content specifically:

  • Very High volatility: Anything mentioning specific AI models, LLM tools, SDK versions, device specs, pricing pages, compliance content
  • High volatility: Comparison pages (competitors update features), "best tools" lists, automation framework tutorials (Selenium 4.x, Playwright updates)
  • Medium volatility: Mobile testing how-tos, emulator guides, CI/CD integration guides
  • Low volatility: Core concepts (what is Appium, what is real device testing), fundamentals

Step 3 — Staleness Score

For each page, calculate a staleness score (1–10):

Age component (max 5 points):

  • Published < 6 months ago: 0
  • 6–12 months: 1
  • 12–18 months: 2
  • 18–24 months: 3
  • 24–36 months: 4
  • 36 months: 5

Volatility multiplier:

  • Very High: age score × 2
  • High: age score × 1.5
  • Medium: age score × 1
  • Low: age score × 0.5
  • Stable: age score × 0.25

Cap at 10.

Staleness verdict:

  • 0–3: Leave Alone (still fresh)
  • 4–6: Monitor (schedule review in 3 months)
  • 7–8: Refresh (update within 1 month)
  • 9–10: Refresh Now (update this week — ranking at risk)

Step 4 — GSC Freshness Signal Check

If GSC MCP available, for each page check:

  • Impression trend: is it declining over last 90 days vs prior 90 days?
  • CTR trend: declining CTR on a stable-ranking page = content looks stale to searchers
  • Position trend: gradual position loss with no algorithm change = freshness signal

Pages with: high staleness score AND declining GSC trend = Refresh Now (urgent).


Step 5 — Generate Refresh Instructions

For every Refresh Now and Refresh page, output specific instructions:

Page: [URL]
Published: [date] | Last Modified: [date]
Topic volatility: [Very High / High / Medium / Low]
Staleness score: [X/10]
GSC trend: [Impressions UP/DN X% | CTR UP/DN | Position change]
Verdict: REFRESH NOW

What to update:
1. [Specific outdated section or claim — be precise]
2. [Statistics or data points that need new sources]
3. [Tool/version references that are outdated]
4. [New angle or section to ADD based on current state of the topic]

What to keep:
- [Sections that are still accurate and performing]

Effort estimate: [Low (30 min) / Medium (2 hrs) / High (full rewrite)]
Priority: [score based on traffic × staleness]

Output Format

Freshness Audit Summary Table

URL Published Last Modified Topic Volatility Staleness GSC Trend Verdict
/blogs/... 2023-03 2023-03 AI testing tools Very High 9/10 Imp -34% Refresh Now

Sort by: Refresh Now first → Refresh → Monitor → Leave Alone. Within each group: sort by impressions (highest first).

Refresh Now List (Action This Week)

Full instructions per page as formatted in Step 5.

Monitor List

Pages to schedule for review in 3 months. No action needed now — set calendar reminder.

Leave Alone List

Pages that are fresh or stable. No action.


Quick Check: Content Signals for AI Citation Freshness

Beyond dates, LLMs deprioritise content that:

  • References deprecated tools or removed features
  • Uses outdated terminology (e.g., FID instead of INP for Core Web Vitals)
  • Cites statistics from >2 years ago without noting the date
  • Describes a product's old interface vs current

Flag any of these patterns if spotted while auditing.

Install via CLI
npx skills add https://github.com/anandan-digital-marketer/seo-agent-skills --skill 2d-content-freshness-auditor
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