blog-cannibalization

Featured

Detect keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports local-only mode (grep-based) and DataForSEO API mode (Page Intersection endpoint at ~$0.01/call). Outputs severity-scored report with merge or differentiate recommendations. Use when user says "cannibalization", "keyword overlap", "competing pages", "duplicate keywords", "cannibalize".

Data & Documents 1,491 stars 260 forks Updated 3 days ago MIT

Install

View on GitHub

Quality Score: 99/100

Stars 20%
100
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Blog Cannibalization - Keyword Overlap Detection Detect when multiple blog posts compete for the same search keywords. Two modes: local-only analysis (default) and DataForSEO API mode for SERP-level data. ## Two Modes | Mode | Flag | Cost | Data Source | |------|------|------|-------------| | Local | (default) | Free | File content analysis via Grep/Read | | API | `--api` | ~$0.01/call | DataForSEO Page Intersection + Ranked Keywords | Local mode works without any API keys. API mode requires DataForSEO credentials set as environment variables: `DATAFORSEO_LOGIN` and `DATAFORSEO_PASSWORD`. ## Local Mode Workflow ### Step 1: Scan Blog Files Use Glob to find all content files in the target directory: - Patterns: `**/*.md`, `**/*.mdx`, `**/*.html` - Skip files in `node_modules/`, `.git/`, `drafts/` ### Step 2: Extract Primary Keywords For each file, read and extract keyword signals from: - **Title tag** or H1 heading (highest weight) - **H2 headings** (medium weight) - **First paragraph** (supporting signal) - **Meta description** if present in frontmatter Primary keyword extraction method: 1. Tokenize title, H1, H2s, meta description, and first paragraph into 1-gram, 2-gram, and 3-gram phrases. 2. Normalize deterministically: lowercase, remove locale-aware stop words, lemmatize or stem consistently, preserve product names, and keep intent modifiers such as "best", "pricing", "vs", "review", "template", and year. 3. Score sections separately: title/H1 highest...

Details

Author
AgriciDaniel
Repository
AgriciDaniel/claude-blog
Created
5 months ago
Last Updated
3 days ago
Language
Python
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category