Count symbols such as @, #, $, %, operators, slashes, pipes, and currency signs while grouping them into social, finance, math, email, and programming categories.
Symbol Counter converts raw pasted text into a clear analytics report. It shows the main count, supporting metrics, density, and an interpretation that helps you decide whether the text needs cleanup or review.
All processing happens locally in the browser. No server upload is required for pasted text.
Example input: Email dev@example.com about #Launch. Budget is $500 + 20% buffer. Use path /api/v1/users?id=10.
Symbol Counter uses deterministic character matching and script-aware checks where applicable. It also calculates total characters, lines, density, frequency, and category-specific quality signals.
Language detection is heuristic, not a full linguistic classifier. For legal, academic, or production validation, review the exported report manually.
Paste the text and run the tool. It counts symbols by category and frequency.
Yes. Programming symbols such as braces, brackets, operators, pipes, slashes, and angle brackets are grouped separately.
Use Extract Symbols mode and review the currency symbol category in the report.
The tool can remove symbol characters or show only symbol-heavy sections for cleanup.
The automatic classification uses symbol density and symbol categories to estimate the content type.
| Module | What it checks |
|---|---|
| Symbol scanner | Counts non-alphanumeric symbol characters. |
| Category grouping | Separates currency, math, programming, and social symbols. |
| Content classifier | Estimates whether text resembles code, finance, email, or social content. |
| Density metric | Shows symbol weight in the full text. |