content-refresh

content-refresh is a skill for Claude Code, Codex from indranilbanerjee/contentforge. It costs 177 tokens per session (4,053 once invoked), scanned A, original, MIT.

A workflow for updating an existing article with newer research, statistics, sources, and search terms while preserving useful sections and links. It supports light, medium, and heavy rewrite levels.

In plain words
What is it for?
Use it to refresh aging articles, replace outdated claims and examples, update citations and keywords, preserve the URL structure, and rerun quality checks.
Why use it?
It helps keep older content accurate and competitive without unnecessarily rewriting sections that still work.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the contentforge plugin — 22 skills, 9 commands, 13 agents shipped together

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 skills/indranilbanerjee/contentforge/content-refresh
Any agent
npx skills add indranilbanerjee/contentforge --skill content-refresh
Clone the repo
git clone --depth 1 https://github.com/indranilbanerjee/contentforge

Made for: Claude Code, Codex.

Or install contentforge, the plugin that ships this one along with the rest of its 22 skills, 9 commands, 13 agents.

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 content-refresh

README.md
[![agentmods](https://agentmods.dev/badge/skills/indranilbanerjee/contentforge/content-refresh.svg)](https://agentmods.dev/skills/indranilbanerjee/contentforge/content-refresh)
Your own site
<a href="https://agentmods.dev/skills/indranilbanerjee/contentforge/content-refresh"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/contentforge/content-refresh.svg" alt="Measured on agentmods" height="20"></a>
Per session 177 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,053 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 $0.00177 $0.04053
Opus 5 $0.00088 $0.02027
Sonnet 5 $0.00035 $0.00811
Haiku 4.5 $0.00018 $0.00405

Measured 4d ago against content hash bb1d503ea6e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

content-refresh 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 4d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/content-refresh/SKILL.md · 393 lines

How it starts

The opening of the file, as written. The whole thing — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Refresh Workflow

Re-optimize existing content with updated research, current statistics, new sources, refreshed SEO keywords, and Phase 6.5 humanization — while preserving what's working and maintaining search rankings.

When to Use

Use /contentforge:content-refresh when:

  • Content is 6+ months old and needs updated stats/examples
  • Search rankings are declining (lost top 10 position)
  • Competitor content has surpassed yours
  • Product/service features have changed
  • Industry landscape has shifted
  • Content scored well originally (≥7.0) but needs freshening

What This Command Does

  1. Load Existing Content — Read the current .docx from wherever the brand's tracking.backend stores it (local filesystem, Airtable attachment, or Google Drive)
  2. Analyze What to Keep — Identify evergreen sections, high-performing segments
  3. Research Updates — Find current statistics, new sources, recent examples
  4. Selective Rewrite — Update outdated sections, preserve working content
  5. Re-run Quality Gates — Fact-check new claims, re-humanize, re-score
  6. SEO Preservation — Maintain target keywords, internal links, meta structure
  7. Version Control — Save as v1.1, v1.2 (never overwrite v1.0)

Required Inputs

Existing Content:

  • Google Drive URL or File ID
  • OR: Local .docx file path

Refresh Scope (select one):

  • Light Refresh (20%): Update statistics, examples, citations only
  • Medium Refresh (50%): Rewrite intro/conclusion, update 3-5 sections, add new research
  • Heavy Refresh (80%): Complete rewrite using original as outline, keep only evergreen insights

Optional:

  • New target keywords (if pivoting focus)
  • Sections to preserve (mark as "DO NOT EDIT")
  • Deadline (for priority ranking in batch)

How to Use

Basic Usage

/contentforge:content-refresh https://docs.google.com/document/d/XYZ123

Prompt: "What refresh scope? (light / medium / heavy)"

With Scope Specified

/contentforge:content-refresh https://docs.google.com/document/d/XYZ123 --scope=medium

Read the full file on GitHub · 393 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. 4d ago First seen · 393 lines · 177 tokens per session scan A bb1d503ea6e8

Subscribe to this mod's changes

content-refresh is a skill published in the GitHub repository indranilbanerjee/contentforge (26 stars, last pushed 17d ago), licensed MIT. It adds 177 tokens to every session and 4,053 once invoked, about $0.0009 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 2026-08-30.

Related

Other skills, from other repositories

aeo-audit

Audit how a brand appears across the 6 canonical AI answer surfaces — ChatGPT, Perplexity, Google AI Mode, AI Overviews, Gemini, Copilot — probing 10-25 queries into a numbered output bundle with per-platform visibility scorecards, citation-accuracy checks, a competitor matrix, content gaps, and an optimization…

indranilbanerjee/digital-marketing-pro · 173 tokens

backlink-gap

Find referring domains that link to your competitors but not to you, ranked by an outreach-priority score (0.40 DR + 0.25 link-overlap + 0.20 traffic + 0.15 topical relevance) — outputs a four-gate quality scorecard, a 30-prospect outreach shortlist, broken-link candidates, and pre-filled outreach templates. Triggers…

indranilbanerjee/digital-marketing-pro · 178 tokens

ab-test-plan

Design a statistically rigorous A/B or multivariate test plan — If/Then/Because hypothesis, control and variant specs, required sample size per variant (absolute vs relative MDE via sample-size-calculator.py), test duration, guardrail metrics, stopping rules, and go/no-go decision criteria. Triggers on…

indranilbanerjee/digital-marketing-pro · 140 tokens

aeo-geo

Strategy module for Answer Engine / Generative Engine Optimization — audits AI visibility, restructures content for citation, runs entity-consistency checks across Knowledge Graph, Wikidata, Wikipedia, Crunchbase, and LinkedIn, and produces JSON-LD schema specs, monitoring frameworks, and a 90-day LLM content…

indranilbanerjee/digital-marketing-pro · 156 tokens

analytics-insights

Marketing measurement module — builds KPI trees per business model, reporting templates (weekly, monthly, QBR, campaign), anomaly root-cause diagnosis, MMM and incrementality guidance, dark-social tracking, and privacy-first cookieless measurement architecture, including the GA4 AI Assistant channel group for…

indranilbanerjee/digital-marketing-pro · 152 tokens

audience-intelligence

Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on…

indranilbanerjee/digital-marketing-pro · 162 tokens