---
name: content-update-prioritization
description: Prioritizes updates to existing marketing content by combining freshness, audience value, business importance, performance, evidence risk, effort, and dependencies into a transparent action queue. Use for content refresh planning, editorial maintenance, SEO updates, or content backlog prioritization.
license: Apache-2.0
metadata:
  adlass.categories: "marketing-content/seo-web, marketing-content/content-production"
  adlass.industries: ""
  adlass.tags: "content-refresh, prioritization, seo, editorial-backlog, freshness, maintenance"
  adlass.adaptation: "mapping"
  adlass.source: "original"
  adlass.version: "1"
---

# Content update prioritization

## Purpose

Create an evidence-based queue for updating existing content, making trade-offs between audience value, risk, effort, dependencies, and business importance visible.

## Scope

The skill covers inventory, staleness, evidence risk, performance, effort, dependencies, action type, and priority rationale.

**Excluded:** editing the content, changing metrics, and assuming that low traffic alone justifies retirement.

## Data basis

- Content inventory and performance data in scope.
- Business priorities, freshness rules, product facts and team capacity supplied or in scope.

## Result

A prioritized update queue and decision brief.

## Quality criteria

- Every item has cited evidence for urgency, value and effort.
- Priority criteria are explicit and reproducible.
- Update, expand, merge, monitor and retire are distinct actions.
- Uncertain items are separated from high-confidence priorities.

## Instructions

Use the company's rules for freshness and risk. Consider audience usefulness, product change and evidence decay together. Keep measured facts beside qualitative judgments. Do not fabricate scores; show formulas or label qualitative ratings.

## Adapt before use

- Map inventory, performance, date, owner and effort fields.
- Define freshness, risk, priority and retirement rules.
- Add business priorities, capacity and product-change sources.
- Keep source facts, analysis, recommendations, and unresolved questions visibly separate.
- Preserve stable document, section, page, sentence, URL, or row identifiers in every finding.
- Record assumptions about audience, channel, period, approval status, and data coverage.
- Treat missing guidance as an adaptation gap rather than inventing a company rule.
- Prefer a precise, bounded recommendation over a broad generic rewrite.
- Use supplied terminology consistently across the document, sheet, and any derivative copy.
- Do not infer performance, customer behavior, product capability, or market response from wording alone.
- Make every unresolved issue actionable by naming the missing decision, evidence, owner, or source.
- Keep factual claims traceable even when the final copy is concise.
- Recheck that counts, names, dates, and identifiers match across all outputs.
- Mark hypotheses as hypotheses and preserve competing explanations when evidence is mixed.
- Use the stated acceptance criteria as the final completeness check.