2d content freshness auditor

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 Identify which pages are losing relevance due to age, outdated information, or topic evolution — and tell the team exactly what needs to change.

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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

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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Topic volatility = how fast the content becomes outdated.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Stable	Fundamental concepts, historical content	3+ years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

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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)

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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).

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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]

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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.

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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.