Topic Coverage Completeness Checker
Compare your content's subtopic coverage against an ideal topic map built from top-ranking competitors.
Install
pip install -r requirements.txtRun
python topic_coverage_completeness.py --my-url https://mysite.com/post --competitor-urls https://a.com https://b.com --keyword "crm software" --output coverage.xlsxExport
Add --output report.xlsx to save results as a spreadsheet.
| Flag | Description |
|---|---|
--my-url required | My url |
--competitor-urls required | Competitor urls. Multiple values allowed |
--keyword | Keyword |
--output | Output |
python topic_coverage_completeness.py --helpRun across all your blog posts to score quality. Sort by score in the XLSX export, then prioritize rewrites for the lowest-scoring pages.
Before publishing freelance content, run this tool to check quality signals. Use specific metrics as concrete feedback for writers.
Include the analysis in your SEO audit report. Clients appreciate data-backed recommendations over subjective opinions.
Combine with other tools for a complete workflow:
Requires: beautifulsoup4, numpy, pandas, requests, scikit-learn. All included in requirements.txt.
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AAIO Inc — aaioinc.com/tools/topic_coverage_completeness/