Perform high-performance real-time computational text analytics 100% in-browser with zero external API calls or server leaks. Calculate multi-word phrase density across 1-word unigrams, 2-word bigrams, 3-word trigrams, and 4-word four-grams with configurable stop-word filtering. Audit content against Google Helpful Content over-optimization and keyword stuffing penalties with real-time health indicators (Under-Represented <0.8%, Optimal 1.0%–2.5%, Warning 2.6%–3.5%, and Stuffing Hazard >3.5%). Features comprehensive editorial telemetry (characters, words, Type-Token Ratio lexical diversity, Flesch readability, reading and speaking pace), an interactive in-text keyword highlighter, target keyword strategic placement inspector (intro, headings, conclusion), and a 1-click shareable 1200×630 audit dossier card canvas generator.

Universal Keyword Counter & Density Matrix

High-performance real-time computational text analytics studio. Calculate multi-word phrase density, audit keyword distribution against SEO over-optimization penalties, evaluate reading metrics, and inspect target keyword placement across your content.

Total Words & Chars 📝

0 Chars • ~0s Read

Top Keyword & Density 🎯

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0.00% No Data

Lexical Diversity (TTR) 🧬

0.0%

0 Unique Words • Awaiting Text

Keyword Stuffing Radar 🛡️

0 Flags

🟢 Safe Balance

⚡ Quick Test Presets:

Load sample text & focus keywords to test real-time analytics

Content Stage & Controls Real-Time Parser

Characters: 0 (0 no spaces) Sentences: 0 Paragraphs: 0

🎯 Target Focus Keywords (Comma-Separated)

⚙️ Density Engine Parameters Filter Out Common English Stop Words (the, and, of, in...) Case-Sensitive Phrase Matching

Min Word Length:

Min Frequency:

Custom Exclusions (Comma-Separated Words):

Rank	Keyword / Phrase	Count	Density	SEO Health	Action
Enter or paste text into the editor to generate the real-time keyword matrix.

Active Keyword: None Selected

0 of 0

Paste text in the editor to inspect in-text keyword positioning.

📍 Critical Zone Keyword Prominence

Search engines prioritize keywords found in natural, strategic zones over repetitive repetition throughout body text.

First 100 Words (Intro) None

Primary focus keyword should appear in the opening hook.

Headings (# / H1-H3) 0 Found

Structural headings signal core topical entities.

First Sentence Title Hook Missing

Presence in the very first sentence establishes immediate contextual clarity.

Concluding Summary (Last 10%) None

Reinforces main topic authority in the closing thoughts.

🎯 Target Keywords Placement Matrix

Enter target focus keywords in the left column to view dedicated strategic placement verification.

Flesch Reading Ease

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Awaiting input

Flesch-Kincaid Grade

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Estimated reading grade

Estimated Speaking Time

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Calculated at 130 WPM speech pace

Avg. Words Per Sentence

—

Sentence flow & cadence

📊 Editorial Vocabulary Distribution

Lexical Diversity (Type-Token Ratio) evaluates vocabulary variety. A diverse vocabulary keeps readers engaged, while repetitive phrasing degrades reader trust.

Card Theme:

High-resolution 1200×630 audit certificate generated 100% in-browser via HTML5 Canvas. Perfect for social sharing, client audits, and editorial archiving.

📚 Keyword Density, Entity Search & Quality Guidelines

Early search engines relied heavily on exact-match word counts to ascertain page topic relevance. Today, modern deep learning algorithms (such as Google RankBrain, Hummingbird, and MUM) map concepts using Knowledge Graphs and Entity Understanding. Rather than repeating one phrase twenty times, high-ranking content organically discusses related sub-topics, entities, synonyms, and natural problem-solving terminology.

According to Google's Search Essentials (formerly Webmaster Guidelines), "keyword stuffing" refers to the practice of loading a webpage with keywords or numbers in an attempt to manipulate search engine rankings. This results in unnatural, clunky reading experiences. Densities exceeding 3.5% trigger automated spam detection filters, resulting in rank demotion or algorithmic indexing suppression.

Single-word (unigram) analysis often provides an incomplete picture because common language utilizes compound phrases (e.g., "artificial intelligence", "customer relationship management", "high-performance computing"). Inspecting 2-word, 3-word, and 4-word n-grams uncovers real contextual cadence and reveals long-tail search intent patterns that single-word counters miss.

The Type-Token Ratio (TTR) calculates the percentage of unique words relative to total words. A TTR above 55% indicates rich, varied prose suitable for comprehensive guides and authoritative articles. A low TTR (under 35%) signals repetitive vocabulary, which can bore readers and signal shallow content to quality evaluators.

Your confidential drafts, client briefs, unpublished manuscripts, and marketing copies are parsed entirely inside your browser's local JavaScript execution context. Zero text strings, IP addresses, or metadata are ever transmitted to any remote server or third-party API.

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