/content-refresh

name: content-refresh
description: "Re-optimize an existing content piece with current statistics, new sources, and fixed citations at light (~20%), medium (~50%), or heavy (~80%) rewrite scope — preserving evergreen sections, SEO keyword placements, the URL slug, and internal links, then re-running the pipeline's quality gates (fact-check, validation, humanizer, reviewer) and saving as a new version with a before/after comparison report; the original file is never overwritten. Triggers on \"/contentforge:content-refresh\", \"update this old article\", \"rankings dropped, refresh this post\", \"this content has outdated stats\", \"refresh it with current data\". Reuses the 10-phase pipeline agents and loads the original .docx from the brand's tracking backend; pairs with /contentforge:cf-audit to find candidates and /contentforge:publish to push the update."
argument-hint: "[content-path or URL]"
effort: high

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 **Selective Rewrite** — Update outdated sections, preserve working content 5.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

Batch Refresh (multiple pieces)

Run the refresh sheet through `/contentforge:batch-process` — point it at a sheet whose rows reference existing documents:

/contentforge:batch-process https://docs.google.com/spreadsheets/d/ABC123

Sheet columns: `doc_url`, `refresh_scope`, `priority`

What Happens

Step 1: Content Analysis (2-3 minutes)

• Load existing content from Google Drive
• Extract metadata (original publish date, current word count, quality score)
• Identify sections: intro, body paragraphs, conclusion, citations
• **Evergreen Detection**: Flag sections that are timeless (definitions, principles, frameworks)
• **Outdated Detection**: Flag statistics >12 months old, broken links, deprecated examples
• Calculate "freshness score" (0-100, based on %outdated)

**Output:**

Content Analysis Report
─────────────────────────────────────────────────────
Title: "AI in Healthcare: 2025 Trends and Predictions"
Original Publish: 2025-03-15
Current Word Count: 2,340 words
Original Quality Score: 8.9/10

Freshness Score: 42/100 (Needs Refresh)

Evergreen Sections (Keep):
✓ Para 2: Definition of AI in healthcare
✓ Para 5: Historical context (2010-2020)
✓ Para 8: Ethical considerations framework

Outdated Sections (Update):
⚠ Para 1: Intro references "2025 predictions" (now outdated)
⚠ Para 3: Statistics from 2024 market report
⚠ Para 6: Example of startup acquired in 2025
⚠ Para 10: Conclusion mentions "upcoming 2025 regulations"
⚠ Citations: 6/15 links are broken (404 errors)

Recommendation: Medium Refresh (50% rewrite)
─────────────────────────────────────────────────────

Step 2: Research Phase (Targeted)

• Run Phase 1 (Research Agent) focused ONLY on outdated sections
• Search for: Current statistics (2026), new case studies, recent regulatory changes
• Find replacement sources for broken citations
• **Preserve existing sources** for evergreen content

Step 3: Selective Rewrite

• **Keep evergreen sections unchanged** (no rewrite)
• **Update outdated sections** with new research
• **Rewrite intro/conclusion** to reflect current year, updated predictions
• **Maintain article structure** (same H2/H3 hierarchy)
• **Preserve internal links** and brand-specific terminology

Step 4: Re-run Quality Pipelines

• **Phase 2 (Fact-Checker)**: Verify ONLY new claims and updated statistics
• **Phase 4 (Validator)**: Check for hallucinations in rewritten sections
• **Phase 5 (Structurer)**: Ensure refreshed content flows naturally with preserved sections
• **Phase 6 (SEO)**: Preserve the original keyword **placements** (title, H1, first 100 words, 2-3 H2s, conclusion) and meta structure. Density is monitored for drift and reported — it is advisory, never a target to pad toward.
• **Phase 6.5 (Humanizer)**: Re-humanize rewritten sections
• **Phase 7 (Reviewer)**: Re-score (target: ±0.5 points from original score)

Step 5: Version Control

• Original: `Article-AI-Healthcare_v1.0.docx` (never modified)
• Refresh: `Artic