Keyword Density & N-Gram Frequency Counter
Audit SEO text for optimal keyword frequency, calculate unigram/bigram density percentages, and prevent algorithmic search engine keyword stuffing penalties.
1. Article / Content Draft
2. Frequency & Density Analysis
| Keyword / Phrase | Count | Density | SEO Status |
|---|---|---|---|
| search | 4 | 7.69% | Warning (>4%) |
| engine | 3 | 5.77% | Warning (>4%) |
| optimization | 2 | 3.85% | High (2.5-4%) |
| content | 2 | 3.85% | High (2.5-4%) |
| keyword | 2 | 3.85% | High (2.5-4%) |
About this tool
How to use it
- Paste your SEO article draft, blog post manuscript, or product copy into the text editor.
- Toggle tokenization filters: ignore common stop words (e.g., 'the', 'and', 'with') and words under 3 letters.
- Switch between 1-Word, 2-Word, and 3-Word N-gram phrase tabs to assess multi-word topical keywords.
- Review the calculated frequency count and percentage density for each keyword in the sortable table.
- Check the automated SEO Health Banner to verify whether any keywords exceed the 4.0% keyword stuffing threshold.
- Click 'Copy Density Report' to export the keyword distribution to your clipboard.
Why it matters
Keyword stuffing (repeating target search terms unnaturally) is explicitly penalized by modern search engines like Google under their Spam policies. A healthy keyword density typically ranges between 1.0% and 2.5%. Analyzing 1-word, 2-word, and 3-word N-grams ensures natural topical coverage without triggering algorithmic demotions.
When to use it
Use when optimizing content for organic search, editing freelance SEO copy, preparing product descriptions for Amazon or Shopify, or auditing competitors' ranking articles.
Good to know
Density is calculated as: (Keyword Count / Total Words in Article) × 100. Filtering stop words ensures focus on content-bearing nouns and action verbs rather than grammatical glue words.
Common questions
What is an ideal keyword density for SEO in 2026?
An ideal keyword density for primary target keywords is generally between 1.0% and 2.5%. Densities exceeding 3.5% to 4.0% risk search engine penalties for keyword stuffing.
What are N-grams in keyword analysis?
An N-gram is a continuous sequence of N items from text. A 1-gram is a single word ('shoes'), a 2-gram is a two-word phrase ('running shoes'), and a 3-gram is a three-word phrase ('trail running shoes').
Why should I filter out stop words?
Stop words (like 'the', 'is', 'at', and 'on') naturally appear dozens of times in any English sentence. Filtering them prevents functional grammar from burying your actual commercial topics.
What is lexical diversity?
Lexical diversity measures the percentage of unique words relative to total words. Higher diversity indicates a richer, more engaging vocabulary with less repetitive prose.
Is my unpublished draft stored on your servers?
No. All text parsing, N-gram extraction, and density calculations run 100% locally inside your web browser. Zero article text is ever transmitted online.