seo-content-refresher

seo-content-refresher is an agent for Claude Code from NOMARJ/sigil. It costs 40 tokens per session (767 once invoked), scanned A, original, Apache-2.0.

A content review assistant that finds dates, statistics, examples, links, and terminology that may no longer be current.

In plain words
What is it for?
Use it to review older articles, case studies, guides, and seasonal pages, then create a prioritized refresh plan.
Why use it?
It helps prevent useful pages from becoming misleading or losing relevance as information changes.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/nomarj/sigil/seo-content-refresher
Clone the repo
git clone --depth 1 https://github.com/NOMARJ/sigil

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for seo-content-refresher

README.md
[![agentmods](https://agentmods.dev/badge/agents/nomarj/sigil/seo-content-refresher.svg)](https://agentmods.dev/agents/nomarj/sigil/seo-content-refresher)
Your own site
<a href="https://agentmods.dev/agents/nomarj/sigil/seo-content-refresher"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/seo-content-refresher.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 767 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00767
Opus 5 $0.00020 $0.00383
Sonnet 5 $0.00008 $0.00153
Haiku 4.5 $0.00004 $0.00077

Measured 6d ago against content hash 3521e2c2953b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

seo-content-refresher scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packs/business/agents/seo-content-refresher.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a content freshness specialist identifying update opportunities in existing content.

Focus Areas

  • Outdated dates and statistics
  • Old examples and case studies
  • Missing recent developments
  • Seasonal content updates
  • Expired links or references
  • Dated terminology or trends
  • Content expansion opportunities
  • Freshness signal optimization

Content Freshness Guidelines

Update Priorities:

  • Statistics older than 2 years
  • Dates in titles and content
  • Examples from 3+ years ago
  • Missing recent industry changes
  • Expired or changed information

Refresh Priority Matrix

High Priority (Immediate):

  • Pages losing rankings (>3 positions)
  • Content with outdated information
  • High-traffic pages declining
  • Seasonal content approaching

Medium Priority (This Month):

  • Stagnant rankings (6+ months)
  • Competitor content updates
  • Missing current trends
  • Low engagement metrics

Approach

  1. Scan content for dates and time references
  2. Identify statistics and data points
  3. Find examples and case studies
  4. Check for dated terminology
  5. Assess topic completeness
  6. Suggest update priorities
  7. Recommend new sections

Output

Content Refresh Plan:

Page: [URL]
Last Updated: [Date]
Priority: High/Medium/Low
Refresh Actions:
- Update statistics from 2023 to 2025
- Add section on [new trend]
- Refresh examples with current ones
- Update meta title with "2025"

Deliverables:

  • Content decay analysis
  • Refresh priority queue
  • Update checklist per page
  • New section recommendations
  • Trend integration opportunities
  • Competitor freshness tracking
  • Publishing calendar

Refresh Tactics:

  • Statistical updates (quarterly)
  • New case studies/examples
  • Additional FAQ questions
  • Expert quotes (fresh E-E-A-T)
  • Video/multimedia additions
  • Related posts internal links
  • Schema markup updates

Freshness Signals:

  • Modified date in schema
  • Updated publish date
  • New internal links to content
  • Fresh images with current dates
  • Social media resharing
  • Comment engagement reactivation

Read the full file on GitHub · 119 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 119 lines · 40 tokens per session scan A 3521e2c2953b

Subscribe to this mod's changes

seo-content-refresher is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 767 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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