---
title: Content Freshness Queue
category: product
entity_type: skill
price: $15
canonical: https://forgehouse.ai/skills/content-freshness-queue/
lang: en
hreflang_alt: https://forgehouse.ai/tr/skiller/content-freshness-queue/
last_updated: 2026-06-20
---

# Content Freshness Queue

> Content freshness and refresh queue

Automatically detects content untouched for 90+ days and ranks it into a weekly refresh queue using a five-factor priority score (traffic, age, topical weight, AI citation signal, content-type half-life). It joins your CMS or MDX data with Search Console clicks and AI citation tracking, then renders a dashboard the decision-maker can act on in 30 seconds.

## Use cases
- Deciding whether to write new content or refresh existing pages each month
- Surfacing high-traffic pages whose rankings are quietly decaying
- Prioritizing pillar refreshes that pull supporting cluster articles along with them
- Catching page-2 (positions 11-20) pages that a refresh can push into the top half
- Flagging stale legal, health, or finance pages that carry compliance risk
- Generating a weekly Monday refresh queue via scheduled scan

## Benefits
- Recovers organic traffic that silently leaks from aging content
- Protects AI citation visibility by keeping recency signals strong for answer engines
- Replaces 4-6 hours of manual content audits with a 5-minute automated scan
- Focuses effort on the 20% of pages that drive 80% of traffic via Pareto cohorts

## What’s included
- Sanity GROQ and MDX frontmatter extractors for last-modified and topical entities
- Five-factor priority scoring with content-type half-life weighting (pillar/cluster/evergreen/news)
- Search Console traffic and AI citation count join for accurate prioritization
- Color-coded queue dashboard (fresh / needs refresh / critical) in renderable markdown
- A five-point refresh checklist so updates add real information gain, not just date bumping
- Scheduled full scan plus CMS webhook for incremental queue updates

## Who it’s for
SEO leads and content teams managing a growing library who want refresh decisions driven by data, not guesswork.

## How it runs
Pages age quietly until traffic and AI citations bleed out. A weekly scan joins content age with GSC clicks and citation counts, scores every page on one formula and surfaces the ten most urgent refreshes.
1. Extracts last_modified and topical entities from every content source: a GROQ query against Sanity or frontmatter parsing across an MDX repo, distinguishing real body edits from meta-only edits so a comment tweak does not reset a page's age.
2. Joins two external signals onto that inventory: 28-day clicks per page from Google Search Console and 90-day AI citation counts from the citation tracker, because age alone is a misleading metric.
3. Scores every page with one formula: log-scaled traffic times age times topical weight times an AI-citation multiplier times content-type weight, divided by the type's half-life (pillar 365 days, cluster 180, evergreen 730, news 7).
4. Renders the top 10 as a 30-second decision dashboard: a markdown table with age, monthly traffic, AI citations and a color status (green under 90 days, yellow needs refresh, red critical above score 3.0).
5. Attaches the refresh contract to every recommendation: minimum 5 real changes per page (dateModified schema, one new statistic, one new authoritative external link, one schema enrichment, one new internal link), because date bumping alone fools nobody.
6. Keeps the queue alive automatically: a Monday cron runs the full scan per customer and mails the digest, while a Sanity webhook drops freshly edited pages from the queue the moment a real body change lands.

## FAQ
### I keep content in MDX files, not a traditional CMS. Will it still build a queue?
Yes, it joins CMS or MDX data with Search Console clicks, so a file-based library works fine. It does need Search Console access to weigh traffic and decay properly.

### Does it just flag anything older than ninety days regardless of whether it matters?
No, the ninety-day mark only surfaces candidates, then a five-factor score ranks them by traffic, age, topical weight, AI citation signal and content-type half-life. A quiet old page sinks below a high-traffic one that is slipping.

### Once a page is queued, does it rewrite the content for me?
No, it decides what to refresh and in what order, not the refresh itself. It hands you a ranked queue where pillar items pull their supporting cluster articles along, so you fix a topic as a whole.

## Price
$15, one-time, no subscription. VAT included.

Related guide: [Building a multilingual AI content pipeline](https://forgehouse.ai/guides/ai-content-pipeline/)