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 inte…
Library skill — the default version is maintained in GitHub; edits you make live in your own clone.
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.
| 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.
Use Glob to find all content files in the target directory:
- Patterns: **/*.md, **/*.mdx, **/*.html
- Skip files in node_modules/, .git/, drafts/
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, meta description and H2s medium, first paragraph supporting. 4. Select the top-scoring 2-3 word phrase as the primary keyword and record secondary keywords from H2 headings.
Group posts into clusters using these matching rules (in priority order):
For each cluster with 2+ posts, assess severity and generate a recommendation.
Display the results table and per-cluster recommendations.
Requires the --api flag and a dedicated local CLI wrapper that reads
DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD from the environment and emits
JSON. Do not use WebFetch for DataForSEO POST calls and never expose Basic auth
headers, login, password, or encoded credentials in prompts or reports. If no
wrapper exists in the project, report SKIPPED: DataForSEO wrapper unavailable
and run local mode.
Page Intersection - find keywords where multiple URLs rank:
POST https://api.dataforseo.com/v3/dataforseo_labs/google/page_intersection/live
{
"pages": {
"1": "https://example.com/post-a",
"2": "https://example.com/post-b"
},
"language_code": "en",
"location_code": 2840
}
Cost: ~$0.01 per call. Returns overlapping keywords with position, volume, CPC.
Ranked Keywords - get all keywords a single URL ranks for:
POST https://api.dataforseo.com/v3/dataforseo_labs/google/ranked_keywords/live
{
"target": "https://example.com/post-a",
"language_code": "en",
"location_code": 2840
}
The wrapper sends DataForSEO auth headers from environment variables and never prints them.
Four severity levels based on overlap signals:
| Level | Criteria | Action Urgency |
|---|---|---|
| Critical | Same exact keyword, both pages in top 20 | Immediate |
| High | Same keyword cluster, one page outranks the other | This week |
| Medium | Related keywords with partial SERP overlap | This month |
| Low | Semantic similarity but different confirmed intents | Monitor |
severity_score = overlap_count x avg_search_volume x (1 / position_gap)
Where:
- overlap_count = number of shared ranking keywords
- avg_search_volume = mean monthly volume of shared keywords
- position_gap = absolute difference in average ranking position (min 1)
Higher score = more urgent cannibalization problem.
Without SERP data, use a simplified scoring: - Critical: Exact primary keyword match between posts - High: Stem match on primary keyword, or 3+ shared H2 keywords - Medium: Semantic overlap on primary keyword - Low: Subset match only, or shared secondary keywords
| Post A | Post B | Shared Keywords | Severity | Recommendation |
|--------|--------|-----------------|----------|----------------|
| /best-crm-tools | /top-crm-software | best crm, crm tools, crm software | Critical | MERGE |
| /email-tips | /email-marketing-guide | email marketing | High | DIFFERENTIATE |
| /seo-basics | /seo-for-beginners | seo basics, beginner seo | Critical | CANONICAL |
| /react-hooks | /react-state-mgmt | react, state | Low | NO ACTION |
For each flagged cluster, provide: - Both post titles and URLs - Full list of overlapping keywords (with volume if API mode) - Which post is stronger (more comprehensive, better structured) - Specific recommendation with rationale
Four possible actions for each cannibalization cluster:
When both pages are thin or cover the same intent with similar depth. - Combine the best content from both into one comprehensive post - 301 redirect the weaker URL to the merged post - Preserve all internal links pointing to either URL
When pages serve different intents but keyword targeting overlaps. - Shift the primary keyword of the weaker post to a related long-tail - Update the title, H1, and meta description to reflect the new focus - Add internal links between the two posts to signal distinct topics
When one post is clearly the authority and the other is a lesser duplicate.
- Add rel="canonical" on the weaker page pointing to the authority
- Do not combine canonical and noindex casually. Use noindex only when removal
from search is intended
- Link from the weaker page to the authority page
When a page should be removed from search results but still exist for users. - Confirm the page has no meaningful unique search demand or business value - Keep it crawlable until the noindex directive is observed - Do not use as the default duplicate-content fix
When intent is genuinely different despite surface-level keyword similarity. - Document the reasoning for future audits - Monitor rankings quarterly for any position changes - Re-evaluate if either post drops in rankings