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Every text tool runs entirely in your browser — no upload, no server processing, no account required. Paste or type your text, process it instantly, and copy the result. Your text never leaves your device.
Count words, characters, sentences, paragraphs, and reading time in any text
Convert text between camelCase, PascalCase, snake_case, kebab-case, UPPER_CASE, and more
Remove duplicate lines from any list — case sensitive or insensitive, with sort options
Unlike most online tools, Toolivon processes everything directly in your browser using the Web APIs built into Chrome, Firefox, Safari, and Edge.
Word counters help writers meet editorial requirements. Blog posts average 1,500–2,500 words for SEO, academic essays need 500–5,000 words, and social media captions max out at 150–300 characters. Real-time statistics show progress without switching between apps.
Character counters matter for platforms with strict limits: Twitter (280 chars), LinkedIn headlines (220 chars), meta descriptions (155–160 chars for SEO), SMS messages (160 chars standard), and email subject lines (50 chars for mobile preview). Knowing your count prevents truncation.
Case conversion tools save time when refactoring code. Converting between camelCase (JavaScript), snake_case (Python/Ruby), PascalCase (C#), and kebab-case (URLs/CSS) ensures consistency across codebases. Database column names use snake_case, API endpoints use kebab-case, and class names use PascalCase — converting manually is error-prone.
Duplicate removers clean up imports, dependency lists, and configuration files. SQL queries often need DISTINCT behavior on text data during data migration. Log file analysis requires removing duplicate error messages to count unique issues. Git commit messages need cleaning when cherry-picking or rebasing branches.
Removing duplicate lines is essential for data processing. CSV exports often contain duplicate rows. Email lists need deduplication before sending campaigns to avoid spam complaints. Survey responses require duplicate detection when merging multiple data sources. User-generated content needs cleaning before analysis.
Case-insensitive duplicate removal handles typos: "john@example.com" and "John@Example.com" are the same email. Case-sensitive mode preserves SQL keywords (SELECT vs select) when extracting code snippets. Sorting alphabetically after deduplication makes data easier to review and diff.
Academic institutions enforce strict word counts. Essays (500–1,000 words), term papers (2,000–5,000 words), theses (10,000–20,000 words), and dissertations (40,000–100,000 words) have specific requirements. Most universities accept ±10% variance but flag papers that exceed limits. References and footnotes usually don't count toward word limits.
Reading time estimates help presenters and podcasters. Speech averages 130–150 words per minute for presentations, 180–200 wpm for conversational speech, and 100–130 wpm for formal lectures. A 10-minute presentation needs 1,300–1,500 words. Audio book narration targets 150–160 wpm, while radio ads compress to 60–75 wpm for emphasis.
Meta descriptions need 155–160 characters to display fully in Google search results. Longer descriptions get truncated with "…" which reduces click-through rates. Title tags should stay under 60 characters (580 pixels) to avoid truncation. Character counters with space-removal help fit content within Twitter's 280-character limit while maximizing message density.
Content length affects search rankings. Articles between 1,500–2,500 words perform best for informational queries. Long-form content (2,000+ words) generates more backlinks and social shares but requires higher reader investment. Short content (300–600 words) works for news updates and product descriptions. Word counters help content creators hit optimal targets.
Words are defined as sequences of characters separated by whitespace (spaces, tabs, newlines). This matches Microsoft Word and Google Docs behavior. Contractions like "don't" count as one word. Hyphenated words like "real-time" count as one word. Numbers and URLs count as words. Em dashes and en dashes are treated as word separators.
Sentence counting uses punctuation heuristics: periods, exclamation marks, and question marks end sentences. This approach has limitations — abbreviations like "Dr." and decimal numbers like "3.14" trigger false positives. Advanced algorithms use natural language processing, but simple regex patterns work for 95% of use cases.
camelCase: First word lowercase, subsequent words capitalized, no spaces. JavaScript convention for variables and functions: getUserName, isValidEmail.
PascalCase: Every word capitalized, no spaces. C# and Java convention for classes: HttpRequest, DatabaseConnection.
snake_case: All lowercase, words separated by underscores. Python, Ruby, and SQL convention: user_name, order_total.
kebab-case: All lowercase, words separated by hyphens. URL slugs and CSS class names: blog-post, primary-button.
CONSTANT_CASE: All uppercase, underscores between words. Environment variables and constants: API_KEY, MAX_RETRIES.
Exact matching compares lines character-by-character. Two lines are duplicates only if every character matches, including whitespace. This preserves data integrity but misses near-duplicates like leading/trailing spaces.
Case-insensitive matching normalizes text to lowercase before comparison. "Hello" and "HELLO" are treated as duplicates. This works well for email lists, usernames, and tags where case doesn't matter semantically.
Trimming whitespace removes leading/trailing spaces and tabs before comparison. " hello " matches "hello". This catches duplicates created by copy-paste operations or CSV export quirks. Combined case-insensitive + trimmed matching catches 90% of real-world duplicates.
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