The page word count analyzer calculates the editorial volume of web copy by stripping HTML markup tags, normalizing whitespace, and computing key lexical metrics including total words, total characters, and average word length. Search engine raters and content strategists inspect body copy volume to confirm topical depth and eliminate thin content.

### Lexical Processing Architecture

The tool executes clean text normalization: 1. **Tag Stripping:** All HTML tags are removed using regex substitution (`s.replace(/<[^>]+>/g, ' ')`). 2. **Word Tokenization:** The text is trimmed and split by consecutive whitespace (`split(/\s+/)`). 3. **Metric Calculations:** - Total Words: `words.length` - Total Characters: `text.length` (including spaces) - Average Word Length: Sum of word character lengths divided by total word count (`avg.toFixed(1)`).

### Worked Content Example

Analyzing an excerpt with markup: ```html <h2>Search Optimization</h2><p>High quality content requires depth and clarity.</p> ``` 1. Stripped text: `Search Optimization High quality content requires depth and clarity.` 2. Word count: **9 words** (`['Search', 'Optimization', 'High', 'quality', 'content', 'requires', 'depth', 'and', 'clarity']`). 3. Character count: **68 characters**. 4. Total letter count: 59 letters $\rightarrow$ Average word length: $59 / 9 = \mathbf{6.6\text{ characters/word}}$.

### In-Browser Privacy Note

All text tokenization and regex evaluation execute locally inside your web browser. No draft articles, proprietary copy, or private HTML fragments are transmitted over the network or saved to remote databases.