Free Keyword Density Checker for Text and URLs
Measure word and phrase frequency in pasted text or on a public webpage. Text mode runs in your browser; URL mode asks the TryFormatter server to fetch the public page, then analyzes its readable text.
Ready for Analysis
Enter a URL or text to identify keyword clusters and density.
1. What is Keyword Density and N-Gram Analysis?
Keyword density is a mathematical ratio that measures how frequently a specific word or phrase appears relative to the total number of words within a document. Expressed as a percentage, the formula used here is (Keyword Occurrences ÷ Total Word Count) × 100. Modern search systems do not publish an ideal percentage. Density is best used as an editorial diagnostic for repetition, not as a ranking target.
To accurately understand what an article is about, search engines look beyond isolated single words. They decompose text into N-grams—contiguous sequences of N items from a sample of speech or text. A 1-gram evaluates single terms (e.g., "converter"), a 2-gram evaluates two-word pairs (e.g., "image converter"), and a 3-gram evaluates full phrases (e.g., "free image converter"). Evaluating 2-gram and 3-gram distributions reveals whether your content establishes coherent topic clusters or merely repeats generic vocabulary.
2. Key Use Cases for Density and N-Gram Auditing
Tracking phrase frequencies and term distribution serves multiple practical functions across on-page optimization workflows:
Keyword Stuffing Prevention
Find phrases that read mechanically or dominate a short passage, then review each occurrence in context before publishing.
Competitor Page Reverse Engineering
Analyze top-ranking competitor URLs to extract their dominant 2-word and 3-word phrase frequencies and semantic emphasis.
Stop Word Noise Reduction
Strip out high-frequency prepositions and conjunctions ("in", "the", "and") to isolate high-value subject matter terminology.
Confidential Manuscript Auditing
Check book manuscripts, unannounced press releases, and internal whitepapers in browser memory with zero third-party cloud logging.
3. How to Interpret Density Without Inventing Thresholds
Google documents keyword stuffing as unnatural repetition, but it does not publish a safe density percentage. Interpret the measured value alongside passage length, grammar, and reader usefulness:
| Phrase Category | What to Review | Possible Warning Sign | Editorial Response |
|---|---|---|---|
| Primary Target Keyword (1-Gram) | Does it appear where the topic genuinely needs naming? | The same exact phrase is forced into nearby sentences or headings. | Rewrite the passage for clarity; do not replace precise terms merely to hit a number. |
| Supporting Phrases (2-Gram) | Do repeated pairs add meaning or only echo the same wording? | Several sentences begin or end with the identical pair. | Combine duplicate points or use a clearer pronoun where the reference remains obvious. |
| Long-Tail Expressions (3-Gram) | Is the full phrase necessary each time? | A marketing slogan or exact-match query is repeated unchanged. | Keep the strongest occurrence and write the surrounding explanation naturally. |
| Stop Words & Conjunctions | Toggle filtering to understand how function words affect the list. | Unfiltered results hide the subject terms you meant to inspect. | Filter them for discovery, but remember they still matter to natural grammar. |
4. How to Use the Keyword Density Checker
Follow these four simple steps to analyze your content's term distribution:
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1
Choose Text or URL Mode
Select Text Analyzer to paste working drafts directly, or choose URL Analyzer to inspect an existing live web page.
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2
Select N-Gram Depth & Stop Word Toggle
Pick your analysis granularity (1-Gram for single words, 2-Gram for phrases, 3-Gram for long-tail patterns) and keep Filter Stop Words checked to remove grammatical noise.
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3
Run the Audit
The parser tokenizes the text, counts total and unique words, and computes percentage frequencies. It does not label a percentage as a Google-approved limit.
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4
Review Word Cloud & Refactor
Inspect the interactive tag cloud to visualize topic weight. If secondary terms overshadow your primary topic, adjust subheadings and intro copy accordingly.
5. Concrete Examples: Natural vs Over-Optimized Text
The example below illustrates how repeating a keyword mechanically damages readability, while semantic variation maintains healthy density and high reader value:
| Optimization Style | Sample Text | Density Result | Editorial Assessment |
|---|---|---|---|
| Over-Optimized (Keyword Stuffing) | "If you need a pdf merger, our online pdf merger is the best pdf merger to merge pdf files fast with our pdf merger tool." (26 words) | "pdf merger": 15.4% density (4 times) | Unnatural: The repeated phrase makes the sentence difficult to read and adds no new information. |
| Natural & Semantic (Balanced) | "Combine multiple documents in seconds with our online pdf merger. Select your files, arrange page order, and export a consolidated PDF." (22 words) | "pdf merger": 4.5% in this short snippet (1 occurrence) | Natural: The exact phrase appears once and the remaining verbs explain the workflow. |
6. Why Modern Search Engines Look Beyond Keyword Density
Density can reveal repetition, but Google does not publish an ideal keyword percentage. Modern search systems interpret words in context, so useful coverage matters more than matching a quota:
- Entity Recognition: Search engines recognize that a page about "Apple" containing "M3 chip", "macOS", and "Retina display" is about computers, not fruit.
- Related Concepts: Supporting concepts such as "lossless compression", "dimensions", and "file size" can explain an image topic without repeating one exact phrase.
- Search Intent Fulfillment: Answer the reader's practical question completely instead of padding the page with repetitive variations.
7. Privacy in Text Mode and URL Mode
Text Analyzer mode processes pasted text in the current browser tab. URL Analyzer mode is different: it sends the public URL to TryFormatter's guarded server-side fetch, which follows a limited redirect chain, returns the public HTML with a no-store response, and does not use a third-party CORS proxy.
Do not submit private network addresses, credentials, authentication tokens, or sensitive query parameters. The server must receive the requested public URL to perform the fetch, and hosting or network infrastructure may retain normal request metadata.
Frequently Asked Questions
What is considered a safe keyword density percentage for SEO?
There is no Google-approved safe percentage. Keyword stuffing is about unnatural repetition and low-value wording, not crossing one universal number. Use density to locate repeated phrases, then judge every occurrence in its sentence and page context.
What are N-grams and why should I analyze 2-word and 3-word phrases?
An N-gram is a continuous sequence of N words. While 1-grams analyze single words, 2-grams (e.g., 'image compressor') and 3-grams (e.g., 'compress image online') represent the actual multi-word search queries people type into Google. Checking 2-gram and 3-gram frequencies helps you discover long-tail opportunities and verify phrase balance.
What are stop words and why does this tool filter them out?
Stop words are high-frequency grammatical words such as 'the', 'is', 'at', 'which', and 'on'. Because these words naturally appear dozens of times in every paragraph, they distort frequency calculations. Filtering them allows you to see the real technical, descriptive, and commercial keywords that carry search weight.
How does the URL Analyzer mode work without violating privacy?
The browser sends the public URL to TryFormatter's guarded server-side fetch. It follows a limited redirect chain, returns the public HTML with no-store caching, and the browser removes scripts, styles, navigation, headers, footers, and sidebars before frequency analysis. Do not include secrets or sensitive query parameters because the server and normal hosting infrastructure receive the URL.
Can high keyword density cause a page to be penalized by Google?
A percentage alone does not trigger a documented penalty. Google identifies keyword stuffing through unnatural repetition, lists of terms, and wording added to manipulate rankings. A high density can reveal that problem, but you still need to read the page in context.
How many times should my primary keyword appear in a 1,500-word article?
There is no required count. Use the exact term wherever it is the clearest name for the subject, avoid forcing it into headings or sentences, and prefer useful explanations over repetitions added only to change a percentage.
