Download brain/.raw/sources/claude-blog-skill/skills/blog-rewrite/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does blog-rewrite live?
The publisher keeps it at https://github.com/AgriciDaniel/claude-blog.
Which agents can use blog-rewrite?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
>
name: blog-rewrite
description: >
Rewrite and optimize existing blog posts for Google SEO (May 2026 Core
Update, March 2026 core/spam context, June 2026 spam context, E-E-A-T)
and AI citation visibility as one SEO discipline. Full rewrite for both
Google rankings AND AI citations. For AI-citation-only audit (no Google
work), use blog-geo instead. Replaces fabricated statistics with sourced
data, applies answer-first formatting, adds Pixabay/Unsplash images,
generates built-in SVG charts, validates Article-priority schema, performs AI content
detection, adds citation capsules and information gain markers, and
updates freshness signals. Works with any blog format (MDX, markdown,
HTML). Use when user says "rewrite blog", "optimize blog", "update blog",
"improve blog", "fix blog", "refresh blog post", "blog optimization".
user-invokable: true
argument-hint: ""
license: MIT
Blog Rewriter: Optimize Existing Posts
Rewrites and optimizes existing blog posts for dual ranking: Google search
and AI citation platforms. Preserves the author's voice while applying the
6 pillars of optimization.
Key references:
skills/blog/references/quality-scoring.md - 5-category scoring (Content 30, SEO 25, E-E-A-T 15, Technical 15, AI Citation 15)
skills/blog/references/internal-linking.md - Linking strategy and anchor text rules
skills/blog/references/visual-media.md - Image sourcing and chart styling
skills/blog/references/synthesis-contract.md - 6 LAWs for re-citation hygiene during rewrite (v1.8.0; cross-skill ref lives in the orchestrator's references dir)
skills/blog/references/research-quality.md - cross-source clustering for replacement-statistic research (v1.8.0)
Cross-reference
For 21 evidence-led optimization prompts (AI-detector test, CTR audit, schema, PAA rewording, technical audit, ChatGPT visibility) directly applicable to rewrite work, see /blog flow optimize.
Workflow
Phase 1: Audit (Read-Only)
Read the blog post - Detect format (MDX, markdown, HTML)
Run the quality checklist against skills/blog/references/quality-scoring.md:
Count fabricated vs sourced statistics
Check answer-first formatting (H2 -> stat in first sentence?)
Count images and charts (type diversity?)
Measure paragraph lengths (any > 150 words?)
Check heading hierarchy (H1 -> H2 -> H3, no skips?)
Check schema presence and validity, prioritizing Article/BlogPosting, Person, Organization, and BreadcrumbList; FAQPage is optional entity markup only
Burstiness score - Measure sentence length variance across the post. Low
variance (most sentences within 3-5 words of each other) is a strong AI signal.
Calculate: standard deviation of sentence word counts. Target SD > 6.
Known AI phrase scan - Check for these high-frequency AI phrases:
"in today's digital landscape", "it's important to note", "dive into"
"game-changer", "navigate the landscape", "revolutionize", "seamlessly"
"cutting-edge", "harness the power of", "leverage" (as verb)
Vocabulary diversity - Calculate Type-Token Ratio (TTR): unique words /
total words. Low TTR (< 0.40) suggests AI-generated repetitive phrasing.
Target TTR > 0.50 for natural prose.
AI content percentage estimate - Based on burstiness, phrase density, and
TTR, estimate what percentage of the content reads as AI-generated (0-100%).
Report as: "AI content estimate: ~X%"
Second-order structural reflex scan (v1.8.0) - The first-order checks above
are vocabulary-level. The second-order pass catches what survives them: structural
and rhythmic tics LLMs default to after the obvious words are replaced. Run against
skills/blog/references/ai-slop-detection.md. Flag at minimum:
Question-cadence H2s above 70% of headings
Three or more "Here..." paragraph openers
Three-clause sentence rhythm above 50% in any 200-word window
More than 2 hedge words ("may," "often," "typically," "generally") in any 20-word span
More than 2 wrap-up rhetorical questions ("What does this mean for...?")
More than half of H2 openers starting with a transition word
"The key insight is..." or "What's important here is..." as sentence openers
Listicle pre-list intro above 250 words
Opening-word repetition: top three first-words above 25% share
Paragraph-shape SD below 25 (visual monotony)
A draft is only "AI-detection clean" when both passes are clean. The two-namespace
terminology (first-order/second-order for slop-detection vs Tier 1/2/3 for source
authority) is intentional: see skills/blog/references/ai-slop-detection.md for
why the labels diverged in v1.8.1.
Video embed check:
Count existing YouTube embeds in the post
If 0 embeds, flag: "No video embeds. Consider adding relevant high-quality YouTube embeds when they add useful context."
If present, check: lazy loading? aria-labels? noscript fallback? VideoObject schema?
Cannibalization check:
Identify the post's primary keyword from title, H1, and first paragraph
Search the blog directory for other posts targeting the same keyword:
Grep headings and meta descriptions across all blog posts
Flag any posts with significant keyword overlap
If cannibalization found, report:
Which posts compete for the same keyword
Recommend: merge (combine into one stronger post) or differentiate
(shift one post to a related but distinct keyword)
Calculate current score across 5 categories:
Score across 5 categories (Content Quality 30, SEO Optimization 25, E-E-A-T Signals 15, Technical Elements 15, AI Citation Readiness 15)
Total: 0-100
Present audit summary with specific findings, AI detection results, video status, cannibalization status, and score
Enter plan mode - Present section-by-section optimization plan
Wait for user approval before proceeding.
Phase 2: Research
Identify the blog's core topic from existing content
Find replacement statistics for any fabricated/unsourced data:
Search: [topic] study 2025 2026 data statistics
Target tier 1-3 sources only
Find images if post has fewer than 3:
Prefer original screenshots, product visuals, diagrams, or data graphics when available
For stock, use official provider APIs such as Openverse, Unsplash, Pexels, or Pixabay so license, creator, source URL, and download URL are captured
Download approved assets locally, store attribution, and reject javascript:, data:, and file: URLs
If blog-image is available, offer AI generation for missing or insufficient images and record the selected model ID
Plan charts if post has fewer than 2:
Identify data suitable for visualization
Select diverse chart types
Phase 3: Chart Generation (Built-In)
When the post needs more visual elements, invoke the blog-chart sub-skill:
Select chart type using the diversity rule (no repeated types per post)
Pass: chart type, title, data values, source, platform format
Embed the returned SVG directly within a <figure> wrapper
Target 2-4 charts per 2,000-word post
See skills/blog/references/visual-media.md for chart type selection and styling rules.
Phase 4: Content Rewrite
Apply changes in this order:
4a. Preserve What Works
Keep the author's voice and unique perspective
Preserve original insights and first-hand experience
Keep existing quality images and charts
Maintain internal links
4b. Fix Frontmatter
Add lastUpdated: "YYYY-MM-DD" (today's date)
Keep original date unchanged
Fix meta description: fact-dense, 150-160 chars, includes 1 statistic
Add coverImage + coverImageAlt + ogImage if missing
Search Pixabay/Unsplash/Pexels for wide hero image (1200x630)
Or generate custom SVG cover via blog-chart (text-on-gradient with key stat)
Or generate custom AI image via blog-image sub-skill when available; record the model ID
Verify tags/categories are appropriate
4c. Apply Answer-First Formatting
Every H2 section MUST open with a 40-60 word paragraph containing:
At least one specific statistic with source attribution
A direct answer to the heading's implicit question
4d. Replace Fabricated Statistics
Search for patterns: "X% of...", "X out of Y...", unsourced claims
Replace with real data from tier 1-3 sources
Always include the full FLOW evidence triple: year anchor in prose, inline citation with publisher + document title/report name, and a source block entry with full URL + retrieval date
4e. Improve Headings
Convert statement headings to questions where natural (60-70% target)
Keep 2-3 statement headings for variety
Ensure keyword appears in 2-3 headings naturally
4f. Fix Paragraph Length
Split any paragraph > 150 words
Target 40-80 words per paragraph
Ensure each paragraph starts with its most important sentence
4g. Add Visual Elements
Embed new images after H2 headings, spaced evenly
Embed charts within relevant sections
If blog-image is available: generate custom images for sections lacking good stock matches, prefer the current image model registry, and record the model ID
Adapt embed format to detected platform (MDX vs markdown vs HTML)
4h. Add Video Embeds
If the post lacks YouTube video embeds:
Search 2-3 relevant videos using quality criteria from skills/blog/references/video-embeds.md
Embed using platform-appropriate format (srcdoc lazy loading)
Place: 1 after introduction, 1-2 in mid-article sections
Include noscript fallback for AI crawlers
4i. Add/Improve FAQ
If the query set warrants it and no FAQ exists, add one (3-5 questions)
If FAQ exists, ensure answers are 40-60 words with verified statistics
FAQPage is optional entity markup only. Google FAQ rich results have been limited primarily to well-known, authoritative government and health sites since the 2023 guidance, so do not make FAQPage a core Google rich-result gate.
4j. Reduce Self-Promotion
Max 1 brand mention (author bio context only)
Remove "At [Company], we..." patterns
Convert promotional sections to educational content
4k. Citation Capsule Injection
For each H2 section, generate (or improve existing) a citation capsule:
40-60 word self-contained passage per H2
Contains: one specific claim + one data point + source attribution
Written in a declarative style so an AI system could extract and quote it directly
Placed naturally within the section body, not as a separate callout
Example:
According to a 2026 Gartner study, 58% of enterprise buyers now consult AI
assistants before contacting a vendor ([Gartner](https://www.gartner.com), 2026).
This shift means B2B content must answer specific questions concisely enough
for AI systems to extract and cite in their responses.
Capsules map to the "AI Citation Readiness" category (15 points) in
skills/blog/references/quality-scoring.md.
4l. Anti-AI-Detection Patterns
Apply these transformations to reduce AI-detectable writing patterns:
Eliminate em dashes - Replace every U+2014 character with a comma, hyphen,
colon, or period. Split sentences if needed. Em dashes are an AI writing tell.
Replace flagged phrases - Swap every detected AI phrase (from the scan in
Phase 1 step 3) with a natural alternative. Examples:
"it's important to note" -> "worth noting" or "keep in mind"
"in today's digital landscape" -> "right now" or "in [specific year]"
"leverage" -> "use", "apply", "take advantage of"
"delve" -> "look at", "explore", "dig into"
"robust" -> "strong", "solid", "reliable"
"crucial" -> "key", "essential", "critical" (or restructure the sentence)
Vary sentence length deliberately - After rewriting, scan each paragraph.
Inject short punchy sentences (5-10 words) between longer ones (18-25 words).
Target: no more than 3 consecutive sentences within 5 words of each other's length.
Inject rhetorical questions - Add at least one rhetorical question every
200-300 words to break up declarative monotony.
Use contractions naturally - Replace formal constructions with contractions
where they sound natural: "it is" -> "it's", "we have" -> "we've",
"do not" -> "don't", "is not" -> "isn't".
Include hedging language - Sprinkle first-person hedges that signal real
experience: "in our experience", "we've found that", "from what we've seen",
"this tends to", "it depends on".
4m. Summary Box (Key Takeaways)
If the post lacks a summary box, add one immediately after the introduction:
> **Key Takeaways**
> - [Core finding with statistic and source]
> - [Second key insight or recommendation]
> - [Third actionable takeaway]
> (3-5 bullets, 40-60 words combined. Self-contained - reader gets
> the core value without reading the full article.)
Default label is "Key Takeaways", but this is configurable per persona or
brand voice (e.g., "The Bottom Line", "Quick Summary", "What You Need to Know").
If an existing TL;DR box is present, convert it to the bullet-point Key
Takeaways format. Verify it meets the 40-60 word requirement and contains
at least one statistic with source attribution.
4n. Information Gain Marker Injection
Review the post for original value and tag it:
[ORIGINAL DATA] - Any proprietary data, survey results, experiments, or
case study metrics the author collected first-hand
[UNIQUE INSIGHT] - Novel analysis, contrarian perspectives backed by data
If the post lacks original value markers:
Ask the author for first-hand data or experience to include
At minimum, add analytical insights that connect existing research in new ways
Target: at least 2-3 markers per post
Use HTML comments (``) or visible callouts depending
on the post's style.
Phase 5: Verification
After rewriting, verify all quality gates pass:
Core Quality Gates
Every H2 opens with a statistic + source
No paragraph exceeds 150 words
Zero fabricated statistics
Heading hierarchy is clean
Article-priority schema present and valid; FAQPage only if useful as optional entity markup
Images have descriptive alt text
Cover image present in frontmatter (coverImage + ogImage)
If MDX: build the project to verify no compilation errors
New Element Verification
TL;DR box present after introduction (40-60 words, contains statistic)
At least 2-3 information gain markers present
Citation capsules in major H2 sections (40-60 words, self-contained)
Internal linking zones marked or actual links present (5-10 per 2,000 words)
No AI-detectable phrases remain from banned list
Burstiness and Naturalness Check
Sentence length variance: SD > 6 (mix of short and long sentences)
Contractions used naturally throughout
Rhetorical questions present (1 per 200-300 words)
AI content estimate reduced from audit baseline
Score improved across all 5 categories vs Phase 1 audit
YouTube video embeds present with lazy loading, aria-labels, and noscript fallback
Phase 6: Summary
## Blog Optimization Complete: [Title]
### Score Change
- Before: [X]/100 ([Rating])
- Content Quality: [X]/30
- SEO Optimization: [X]/25
- E-E-A-T Signals: [X]/15
- Technical Elements: [X]/15
- AI Citation Readiness: [X]/15
- After: [Y]/100 ([Rating])
- Content Quality: [Y]/30
- SEO Optimization: [Y]/25
- E-E-A-T Signals: [Y]/15
- Technical Elements: [Y]/15
- AI Citation Readiness: [Y]/15
### AI Detection
- Before: ~[X]% AI-detected content
- After: ~[Y]% AI-detected content
- Phrases replaced: [N]
- Burstiness improved: [before SD] -> [after SD]
### Cannibalization
- [Status: none found / flagged N posts / resolved]
### Changes Made
- [X] statistics replaced with sourced data
- [X] SVG charts added (types: ...)
- [X] images added from Pixabay/Unsplash
- Answer-first formatting applied to [N] H2 sections
- FAQ section updated with [N] questions; FAQPage emitted only as optional entity markup if appropriate
- TL;DR box: [added/updated]
- Information gain markers: [N] ([types])
- Citation capsules: [N] across H2 sections
- AI phrases replaced: [N]
- lastUpdated set to [date]
- Self-promotion reduced to [N] mentions
### Visual Elements
- Charts: [count] ([types])
- Images: [count]
- YouTube videos: [count] ([titles])
### Ready for
- `/blog analyze <file>` to verify final score
- Publishing / deploying
Phase 5.5: Delivery Contract Enforcement (v1.9.0)
Before presenting the rewritten draft, run the 5-gate delivery contract per skills/blog/references/blog-delivery-contract.md. The contract applies to rewrites the same way it applies to new posts: the user is never the first reviewer.
Steps:
Hero check: if the existing post already has a hero image referenced and still on disk, keep it. If the rewrite changed the topic substantially OR the hero is missing, regenerate via python3 scripts/generate_hero.py --topic "<new title>" --tags "<tags>" --out <folder>.
Re-render: run python3 scripts/blog_render.py --md <slug>.md --out-dir <folder> to refresh the .html and .pdf from the updated .md.
Reviewer dispatch: dispatch the blog-reviewer agent against the rendered .html. Threshold: score 90/100 or higher AND zero P0 issues.
Iterate on failure: maximum 3 iterations. After the 3rd failure, STOP and present the diagnostic from <folder>/preflight-report.json.
Rewrites have a higher implicit threshold because the existing draft was presumably already published. Re-presenting something worse than the original is not acceptable. If the rewritten score is lower than the original score, that itself is a P0 condition.
Update Mode
When invoked as /blog update <file>, focus on freshness:
Update statistics to latest available data (2025-2026)
Add new developments since last update
Refresh images if older than 1 year
Update lastUpdated in frontmatter
Preserve the existing structure - minimize rewrites
Target: genuine freshness only. Replace stale statistics, add real new developments, and update lastUpdated/dateModified; do not rewrite to hit a percentage-change threshold.
How do I install blog-rewrite?
Download brain/.raw/sources/claude-blog-skill/skills/blog-rewrite/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does blog-rewrite live?
The publisher keeps it at https://github.com/AgriciDaniel/claude-blog.
Which agents can use blog-rewrite?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.