| 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on "/contentforge:content-refresh", "update this old article", "rankings dropped, refresh this post", "this content has outdated stats", "refresh it with current data".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
- Load Existing Content — Read the current .docx from wherever the brand's
tracking.backend stores it (local filesystem, Airtable attachment, or Google Drive)
- Analyze What to Keep — Identify evergreen sections, high-performing segments
- Research Updates — Find current statistics, new sources, recent examples
- Selective Rewrite — Update outdated sections, preserve working content
- Re-run Quality Gates — Fact-check new claims, re-humanize, re-score
- SEO Preservation — Maintain target keywords, internal links, meta structure
- 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:
Article-AI-Healthcare_v1.1.docx (new version)
- Track changes in metadata: "Refreshed 2026-02-17, updated 6 sections, added 4 new sources"
Refresh Scopes
Light Refresh (~20% rewrite, 8-12 min)
What Changes:
- Update statistics to current year
- Replace 1-2 outdated examples
- Fix broken citation links
- Refresh intro sentence ("As of 2026..." instead of "In 2025...")
- Re-run Phase 6.5 Humanizer only
What Stays:
- All structure (H2/H3 headings)
- 80% of original paragraphs
- All evergreen sections
- Target keywords unchanged
Use Case: Content is 6-12 months old, mostly accurate, just needs stats updated
Medium Refresh (~50% rewrite, 15-20 min)
What Changes:
- Rewrite intro and conclusion completely
- Update 40-60% of body paragraphs
- Add 3-5 new sections for emerging trends
- Replace 50% of citations with current sources
- Re-run Phases 2, 4, 5, 6, 6.5, 7
What Stays:
- Article structure (same H2 sections, order may change)
- Evergreen definitions, frameworks, principles
- Target keywords (may add 2-3 new secondary keywords)
Use Case: Content is 12-24 months old, core thesis is valid but needs significant updates
Heavy Refresh (~80% rewrite, 22-30 min)
What Changes:
- Complete rewrite using original as outline only
- New research from scratch (Phase 1 full run)
- Update target keywords based on current search intent
- Add 5-10 new sections
- Replace 80% of citations
- Full 10-phase pipeline (same as new content)
What Stays:
- Core topic and brand voice
- 1-2 evergreen sections (definitions, historical context)
- SEO URL slug (to preserve backlinks)
Use Case: Content is 24+ months old, industry has changed significantly, needs near-complete overhaul
SEO Preservation Strategies
Keyword Density Maintenance
Original keyword density: 2.3% for "AI in healthcare"
Target for refresh: 2.0-2.6% (±0.3%)
Action: Phase 6 monitors and adjusts rewritten sections
URL Slug Preservation
Original: /blog/ai-in-healthcare-2025-trends
Refreshed: /blog/ai-in-healthcare-2025-trends (SAME URL)
Title updates to: "AI in Healthcare: 2026 Trends and Predictions"
Internal Link Preservation
- All internal links from original content are preserved
- Add new internal links to related updated content
- Never break existing internal link structure
Meta Description Update
Original: "Explore AI in healthcare trends for 2025..."
Refreshed: "Explore AI in healthcare trends for 2026..." (year updated)
Quality Scoring (Refresh vs. Original)
Target: Refresh score should be within ±0.5 points of original
Example:
- Original: 8.9/10 (Content Quality: 9.2, Citations: 8.5, Brand: 9.0, SEO: 8.8, Readability: 9.0)
- Refreshed: 9.1/10 (Content Quality: 9.3, Citations: 9.0, Brand: 9.0, SEO: 8.9, Readability: 9.2)
- Result: ✓ Within acceptable range (+0.2 improvement)
If refresh scores <8.4 (<0.5 below original):
- Flag for human review
- Identify which dimension dropped (likely Citations or SEO)
- Rerun Phase 2 (Fact-Checker) or Phase 6 (SEO Optimizer)
Version Tracking
Metadata in .docx
Document Properties:
Title: AI in Healthcare: 2026 Trends and Predictions
Version: 1.1
Original Publish Date: 2025-03-15
Last Refresh: 2026-02-17
Refresh Scope: Medium (50%)
Sections Updated: 6/12
New Sources Added: 4
Quality Score: 9.1/10 (was 8.9/10)
Refreshed By: ContentForge
Filename Convention
Original: Article-AI-Healthcare_v1.0.docx
1st Refresh: Article-AI-Healthcare_v1.1.docx
2nd Refresh: Article-AI-Healthcare_v1.2.docx
Major Rewrite: Article-AI-Healthcare_v2.0.docx (Heavy Refresh)
Google Drive Organization
ContentForge Output/
└── Article-AI-Healthcare/
├── Article-AI-Healthcare_v1.0.docx (Original, 2025-03-15)
├── Article-AI-Healthcare_v1.1.docx (Refresh, 2026-02-17)
└── refresh-comparison-report.txt
Comparison Report
After refresh, generate side-by-side comparison:
═══════════════════════════════════════════════════════════════
Content Refresh Comparison Report
═══════════════════════════════════════════════════════════════
Article: AI in Healthcare: 2026 Trends and Predictions
Refresh Date: 2026-02-17
Scope: Medium (50%)
Metrics Comparison:
─────────────────────────────────────────────────────────────
Metric │ Original (v1.0) │ Refreshed (v1.1) │ Change
─────────────────────────────────────────────────────────────
Word Count │ 2,340 │ 2,485 │ +145 (+6%)
Quality Score │ 8.9/10 │ 9.1/10 │ +0.2
Citations │ 15 │ 19 │ +4
Broken Links │ 6 (40%) │ 0 (0%) │ -6 (fixed)
Keyword Density │ 2.3% │ 2.4% │ +0.1%
Readability (Grade) │ 11.2 │ 10.8 │ -0.4 (easier)
Freshness Score │ 42/100 │ 95/100 │ +53
Sections Changed:
─────────────────────────────────────────────────────────────
✓ Introduction (completely rewritten)
✓ Section 2: Statistics updated (2024 → 2026 data)
✓ Section 4: New case study added (2026 example)
✓ Section 7: Regulatory update (new FDA guidelines)
✓ Section 9: Predictions updated (2026-2028 outlook)
✓ Conclusion (completely rewritten)
Sections Preserved (Evergreen):
─────────────────────────────────────────────────────────────
Section 1: AI Healthcare Definition
Section 3: Historical Context (2010-2020)
Section 6: Ethical Framework
SEO Impact Assessment:
─────────────────────────────────────────────────────────────
Target Keyword: "AI in healthcare"
Density: 2.3% → 2.4% ✓ (within target)
First mention: Para 1, Sentence 2 ✓ (unchanged)
Meta Title: "AI in Healthcare: 2026 Trends..."
Length: 42 chars ✓ (optimal)
Updated year: 2025 → 2026 ✓
URL Slug: /blog/ai-in-healthcare-2025-trends
Preserved: ✓ (maintains backlinks)
Internal Links: 8 preserved, 3 added ✓
Estimated SEO Impact: +5-10% traffic (fresher content, fixed broken links)
═══════════════════════════════════════════════════════════════
Recommendation: Publish refreshed version, monitor rankings for 2 weeks
═══════════════════════════════════════════════════════════════
Batch Content Refresh
Use Case: Quarterly Content Audit
Agency has 50 blog posts, wants to refresh top 20 performers that are 12+ months old.
Step 1: Prepare Refresh Sheet
doc_url,refresh_scope,priority,notes
https://docs.google.com/.../article-1,medium,1,Rankings dropped from #3 to #7
https://docs.google.com/.../article-2,light,2,Just needs stat updates
https://docs.google.com/.../article-3,heavy,3,Topic outdated, needs rewrite
...
Step 2: Run Batch Refresh
/contentforge:batch-process https://docs.google.com/spreadsheets/d/ABC123
Step 3: Process (standard batch orchestration)
- Sequential — one refresh pipeline at a time. There is no concurrency.
- Queue order is set by the
priority column
- Every phase of every piece is checkpointed, so an interrupted batch resumes where it stopped rather than restarting
- Completion report with before/after scores
Total time scales roughly with the number of pieces and their refresh scope; batching buys queue management and resumability, not a speedup.
Integration with Other Skills
Before Refresh:
After Refresh:
/contentforge:publish — Push updated content to WordPress/Webflow/contentforge:cf-analytics — Track refresh quality scores over time
Limitations
- Content not originally created by ContentForge has no baseline quality score, so the refresh is graded absolutely rather than as a delta — the "±0.5 of original" criterion below does not apply to imported pieces handed over from
/contentforge:cf-audit
- Heavy Refresh (80%) is almost same time as new content (use sparingly)
- Requires the original .docx to be retrievable from the brand's configured tracking backend (can't refresh from published URLs alone)
Success Criteria
Good Refresh:
- Quality score within ±0.5 of original
- Freshness score improves to 85-100
- All broken links fixed
- Keyword placements preserved (density drift reported as advisory)
- SEO rankings stable or improve within 2-4 weeks
Bad Refresh (requires redo):
- Quality score drops >1.0 point
- A keyword placement slot (title, H1, first 100 words, H2s, conclusion) lost its primary keyword
- Internal links broken
- Brand voice inconsistency
Agents Used
The refresh reuses the canonical 10-phase pipeline agents (Reviewer is Phase 7, Output Manager is Phase 8):
- Heavy Refresh — full pipeline, same as new content (Step 0.5 + Phases 1-8)
- Medium Refresh — Phases 2 (Fact-Checker), 4 (Scientific Validator), 5 (Structurer), 6 (SEO/AEO/GEO), 6.5 (Humanizer), 7 (Reviewer), 8 (Output Manager)
- Light Refresh — Phases 6.5 (Humanizer), 7 (Reviewer), 8 (Output Manager)
Related Skills
/contentforge:batch-process — Create or refresh content as a sequential, checkpointed queue/contentforge:cf-variants — A/B test refreshed vs. original elements/contentforge:cf-audit — Find refresh candidates across the whole library
Value: Preserves SEO equity (URL, internal links, keyword placements) while extending content lifespan
