HOMESKILLSBLOGGITHUB
// SKILL

KEYWORD CANNIBALIZATION

Find blog posts that compete against each other. The detector extracts primary keywords from titles and headings, clusters semantically similar targets, and flags posts competing for the same search intent.

$
/blog cannibalization ./content/blog

REQUIRES CLAUDE BLOG INSTALLED IN CLAUDE CODE

// HOW IT WORKS

FIND. CLUSTER. RESOLVE.

Running /blog cannibalization scans all posts in your blog directory. It extracts the primary keyword target from each post's title, H1, and meta description, then uses semantic similarity to cluster posts targeting the same search intent.

For each cluster, you get a recommendation: merge the content, redirect the weaker post, or differentiate the keyword targets. No more posts competing against themselves.

01
KEYWORD EXTRACTION
Extracts primary and secondary keywords from each post's title, H1 heading, meta description, and H2 headings. Builds a keyword profile for every post in your blog.
02
SEMANTIC CLUSTERING
Groups posts with semantically similar keyword targets. Uses text similarity scoring to identify posts that would compete for the same SERP position, even with slightly different wording.
03
INTENT MATCHING
Classifies the search intent of each keyword target (informational, transactional, navigational). Posts with the same intent and similar keywords are the highest-risk cannibalization pairs.
04
MERGE RECOMMENDATIONS
For each cannibalization cluster, recommends whether to merge content into a single comprehensive post, 301 redirect the weaker page, or differentiate by shifting keyword focus.
// USAGE

HOW TO DETECT OVERLAP

Step 1: Install Claude Blog

git clone --depth 1 https://github.com/AgriciDaniel/claude-blog.git && bash claude-blog/install.sh

Step 2: Open Claude Code

claude

Step 3: Run the Detector

/blog cannibalization ./content/blog

Point it at your blog directory. The detector scans all posts, clusters competing keyword targets, and outputs a report with merge/redirect/differentiate recommendations.

// FAQ

QUESTIONS ABOUT CANNIBALIZATION

Keyword cannibalization occurs when multiple pages on your site target the same or very similar keywords. Search engines struggle to determine which page to rank, often resulting in both pages ranking lower than a single, comprehensive page would. It splits your authority and click-through rate across competing pages.
The detector extracts primary keywords from each post's title, H1, H2 headings, and meta description. It then clusters posts with semantically similar keyword targets using text similarity analysis. Posts within the same cluster are flagged as potential cannibalization with a similarity score.
Yes. For each cannibalization cluster, the detector recommends a primary page based on content depth, word count, internal link count, and publication date. It then suggests actions for secondary pages: merge content into the primary, redirect with a 301, or differentiate by adjusting the target keyword.
The base detector works offline using your local blog files. If you have a DataForSEO API key configured, it can also check live SERP rankings to identify which of your pages currently rank for the same queries, providing real-world confirmation of cannibalization issues.
// RELATED SKILLS

EXPLORE MORE

BLOG AUDIT

Full-site blog health assessment with per-post quality scores, orphan detection, and stale content identification.

LEARN MORE →

BLOG STRATEGY

Content strategy planning with topic clusters, competitive gaps, and publishing roadmaps.

LEARN MORE →

BLOG ANALYZE

Deep analysis of individual blog posts with readability scoring, keyword density, and content quality assessment.

LEARN MORE →

VIEW ALL SKILLS →

DETECT OVERLAP
IN 30 SECONDS.

$
git clone --depth 1 https://github.com/AgriciDaniel/claude-blog.git && bash claude-blog/install.sh
VIEW ON GITHUB ALL SKILLS >