Text tools help with the small but repeated jobs that surround writing, editing, coding, research, and content operations. You can count words and characters, change capitalization, compare two versions, find hidden Unicode characters, extract emails and URLs, clean a list, generate text-based ASCII art, analyze writing patterns, or convert Markdown into a PDF.
The best tool depends on the task and the input you have. Start by identifying what you need to change or measure, then choose the narrowest tool that produces the output you need.
Choose a tool by task
Your task | Use this tool | Best for |
|---|---|---|
Count words, characters, lines, or paragraphs | Writing limits, forms, subtitles, reports, and drafts | |
Inspect frequency, density, or character patterns | Text analysis, editing, keyword review, and language checks | |
Change capitalization or naming style | Headings, labels, identifiers, filenames, and code-style names | |
Compare two versions of text | Revisions, configuration files, notes, and content audits | |
Find invisible or unusual characters | Copy-and-paste problems, suspicious spacing, and Unicode debugging | |
Pull emails, URLs, numbers, or identifiers from text | Contact lists, link audits, logs, and structured data collection | |
Remove duplicate lines or format a list | Datasets, tags, inventories, search terms, and line-based text | |
Create decorative text characters | Banners, headings, terminal output, and plain-text layouts | |
Turn Markdown into a PDF | Notes, documentation, reports, and formatted handouts |
You can also browse the complete Text Tools library when your task does not fit one description exactly.
Definitions that make selection easier
A word counter measures basic quantities such as words, characters, sentences, paragraphs, and lines. It may also distinguish characters with spaces from characters without spaces. That difference matters when a form or publishing system imposes a character limit.
A text analyzer examines patterns rather than only totals. Text Statistics can show averages, word frequency, keyword density, and character breakdowns. It is useful when you want to understand how a passage is composed.
A case converter changes the capitalization or naming convention of text. Uppercase and lowercase are familiar editorial transformations, while camelCase, snake_case, kebab-case, and PascalCase are useful for labels and identifiers.
A text diff checker compares two inputs and highlights additions, removals, and changes. A diff is especially helpful when two blocks look similar but may differ in punctuation, spacing, a single value, or a hidden line.
A hidden text detector looks for characters that are difficult to see. These can include zero-width characters, bidirectional controls, soft hyphens, unusual spaces, and other nonprinting characters. Invisible characters are not automatically malicious or incorrect: zero-width joiners and non-joiners can be legitimate in Arabic, Persian, and Indic scripts, as well as in emoji sequences.
A list cleaner treats text as a collection of entries, often one item per line or separated by a delimiter. It can trim whitespace, remove blank or duplicate entries, sort values, add numbering, and apply prefixes or suffixes.
Workflow: count words and characters
Use a word counter when you need a quick, measurable answer about a passage.
Paste or enter the text you want to measure.
Check words, characters with spaces, and characters without spaces.
Review sentences, paragraphs, and lines if the format matters.
Use the reading or speaking estimate as a planning reference.
Export the result as TXT when you need a plain-text record.
For “character count without spaces,” use the metric explicitly labeled without spaces. Do not assume that a word count and a character count use the same definition across every publishing platform. Some systems count line breaks, punctuation, or special Unicode characters differently.
The reading and speaking estimates are useful for planning a presentation, script, or lesson, but they are estimates rather than a guarantee of how long a particular person will take. Dense terminology, long sentences, unfamiliar names, and pauses can all change the actual time.
Workflow: analyze a passage
Text Statistics is the better choice when totals are not enough.
Enter the passage you want to inspect.
Review averages, frequency, density, and the character breakdown.
Adjust case or stop-word options if they better match your question.
Choose a top-10, top-25, or top-50 view for frequency results.
Export TXT or CSV when you need to continue the analysis elsewhere.
This workflow can reveal repeated terms, unusually short or long sentences, and the balance of different character types. It can also help you compare two drafts at a high level before using a diff checker for exact changes.
When interpreting frequency, consider the purpose of the text. A product page may intentionally repeat a product name. A technical document may use the same domain terms frequently. High frequency is a signal for review, not automatically a writing error.
Workflow: clean and format a list
List Cleaner is designed for line-based or delimiter-separated text such as tags, email addresses, filenames, search terms, or inventory values.
Decide how entries are separated: lines, commas, tabs, or another delimiter.
Trim leading and trailing whitespace and collapse unnecessary spacing.
Remove blank entries and duplicates when appropriate.
Sort, reverse, or shuffle the cleaned values if the task requires it.
Add numbering, prefixes, or suffixes, then export the result as TXT.
If your data contains quoted values with commas inside them, use quoted-delimiter parsing rather than treating every comma as a separator. This prevents a value such as "Paris, France" from being split into two entries.
Cleaning can change meaning if applied too aggressively. Do not remove duplicates from a list where repeated values represent quantity, frequency, or separate events. Likewise, do not sort a sequence when its original order carries meaning.
The tool supports up to 100,000 items for its remove/keep operation. For larger or more complex datasets, split the work into intentional batches and verify that the output remains complete.
Workflow: compare two text files
Use Text Diff Checker when you need to compare revisions or investigate a mismatch.
Place the original text in one input and the revised text in the other.
Choose side-by-side or unified presentation.
Review additions, removals, and changed sections.
Enable ignore-whitespace or ignore-case options only when those differences are irrelevant.
Confirm important values manually before accepting the result.
The checker supports common text and structured formats, including TXT, Markdown, CSV, JSON, XML, YAML, YML, and LOG files. For configuration or data files, inspect the surrounding context of each change. A one-character difference in a key, URL, version, or number can have a large effect.
Ignoring whitespace is useful for formatting-only changes, but it can hide meaningful indentation in YAML or spacing in fixed-width text. Ignoring case can also conceal changes in identifiers, commands, or case-sensitive values. Use those options to narrow the review, then turn them off for a final exact comparison.
Workflow: inspect hidden characters
Unexpected spacing, broken matching, or strange copy-and-paste behavior can come from characters that are not visible in ordinary text.
Enter the suspicious text in Hidden Text Detector.
Review the reported zero-width, bidirectional, soft-hyphen, unusual-space, and other nonprinting characters.
Reveal the locations before deciding whether they are expected.
Remove only characters that are unnecessary for your intended use.
Recheck the cleaned text in its destination system.
Be careful with scripts and emoji. Zero-width joiners and non-joiners can form legitimate words or emoji sequences in several writing systems. Bidirectional controls may also be valid in specialized multilingual text, although they deserve extra attention when the displayed order does not match the underlying order.
A useful verification method is to compare the original and cleaned text with Text Diff Checker. If the cleaned result changes more than expected, restore the original and remove characters selectively.
Workflow: extract structured values
Extract from Text is useful when a long passage contains values that you want to collect into a simpler list.
Paste the source text.
Select the value type, such as emails, URLs, phone-like values, numbers, hashtags, mentions, IP addresses, or domains.
Choose deduplication, grouping, case sensitivity, sorting, separators, and location options.
Review the matches in context.
Export TXT or CSV for the next step.
Extraction identifies patterns; it does not establish that every match is valid, current, or safe to contact. Review ambiguous values, especially phone-like strings, domains, and numbers that may belong to dates or product codes.
For a link audit, extract URLs first, deduplicate them, and then review the resulting list. For a contact list, preserve the original source alongside the extracted values so you can trace an entry back to its context.
Workflow: transform formatting or create ASCII text
Case Converter supports 13 modes, including uppercase, lowercase, title case, sentence case, capitalize, toggle, camelCase, PascalCase, snake_case, kebab-case, CONSTANT_CASE, dot.case, and path/case. It preserves Unicode, punctuation, and line breaks where relevant, and can provide a TXT download.
For editorial text, choose title or sentence case and inspect names, abbreviations, and intentional capitalization afterward. For identifiers, choose a naming convention that matches the destination system. A conversion can change spaces and separators, so verify that the result remains a valid identifier before using it in code or a filename.
Text to ASCII creates text-based ASCII art rather than converting an image into ASCII. Choose from 24 FIGlet fonts, set a width from 20 to 500, and adjust horizontal or vertical layout and smushing options. Comment or wrapper formats can help place the result inside source code or terminal output.
ASCII and Unicode are not interchangeable. ASCII is a small character set suited to basic English letters, digits, and symbols. Unicode supports a much broader range of scripts and symbols. Use ASCII art when the destination is a plain-text environment and Unicode when preserving the original language or symbol set matters.
Workflow: convert Markdown to PDF
Markdown to PDF is the server-backed Text tool in this group. It accepts a non-empty UTF-8 .md or .markdown file within the configured limits and supports headings, lists, tables, code, links, safely referenced or embedded images under the tool’s resource policy, Unicode, and Arabic.
Prepare a non-empty Markdown file with a clear structure.
Check headings, list indentation, table separators, code fences, and links.
Submit the file through the tool.
Follow the job status until processing is complete.
Download the resulting PDF and inspect its pages.
Output verification is important because Markdown syntax and PDF layout are different representations. Check that headings have the expected hierarchy, tables remain readable, code does not run beyond the page, links are present, and Arabic or other Unicode text displays correctly.
If the source includes images, confirm that they are available to the document and that the resulting PDF places them correctly. Do not rely only on the source Markdown: review the actual PDF before sharing or archiving it.
Troubleshooting common problems
If a count looks wrong, check whether you need characters with spaces or without spaces. Also review empty-line handling and whether pasted text contains unusual Unicode characters.
If two identical-looking passages produce a diff, inspect whitespace, line endings, punctuation, and hidden characters. Run the text through Hidden Text Detector, then compare again.
If duplicate removal changes the expected result, confirm that repeated lines are truly duplicates rather than meaningful repeated events. Check delimiters before cleaning a list.
If extraction returns too many matches, narrow the value type and inspect locations or surrounding context. Phone-like values and numbers often have legitimate non-contact uses.
If case conversion produces an unexpected identifier, choose the correct naming mode and check acronyms, Unicode letters, punctuation, and line breaks manually.
If a PDF layout is unexpected, simplify the Markdown structure and verify tables, code blocks, links, images, and heading levels one at a time.
Privacy and accessibility considerations
Treat pasted text according to its sensitivity. Before using an online tool, follow the policy that applies to your organization, project, or data. Avoid placing confidential credentials, private personal information, or regulated material into a tool unless you are authorized to do so.
Keep an untouched copy of important source text before cleaning, extracting, or removing characters. This makes it easier to investigate an unexpected result and prevents accidental loss of context.
For accessible text, use descriptive headings, meaningful link text, readable sentence structure, and tables only when they clarify a relationship. Do not communicate important information through capitalization alone. When preparing a PDF, check heading order, table readability, code presentation, and the display of multilingual text.
Plain-text exports can be useful for review and handoff because they make the content easy to inspect in different environments. Always verify the exported file, especially when the text contains multiple languages, symbols, or structured data.
Developer and text-formatting branch
Developers often need the same text operations as writers, but with stricter consequences for small changes. Use Text Diff Checker for source files and structured data, Case Converter for naming transformations, and Text to ASCII for comments, terminal banners, or wrapper-ready text.
Base64 Encoder and URL Encoder belong to the Developer classification rather than Text Tools. Choose those tools when the task is encoding data, not general text cleanup or analysis.
For code and configuration, preserve the original input and avoid ignoring whitespace or case until you know those differences are irrelevant. YAML indentation, JSON punctuation, environment-variable names, and path separators can all be significant. After transforming a value, test it in its intended context when possible.
Frequently asked questions
What are text tools?
Text tools are focused utilities for measuring, inspecting, cleaning, comparing, extracting, formatting, or converting text. Each tool handles a specific operation so you can choose the workflow that matches your input and desired output.
How can I count words and characters online?
Use Word Counter. It reports words, characters with spaces, characters without spaces, sentences, paragraphs, lines, and unique words. It also includes reading and speaking estimates and can export TXT.
What is the difference between a word counter and text statistics?
A word counter focuses on totals and basic measurements. Text Statistics adds frequency, density, averages, and character breakdowns, making it more suitable for analyzing patterns in a passage.
How do I compare two text files online?
Use Text Diff Checker. It supports side-by-side and unified views, highlights additions, removals, and changes, and can load common text and structured file formats.
How do I find zero-width characters?
Use Hidden Text Detector. It identifies zero-width characters and other nonprinting or unusual characters, then lets you reveal their locations and remove selected characters.
How can I remove duplicate lines?
Use List Cleaner. Select the correct delimiter, remove blank entries if needed, enable duplicate removal, and review the output before exporting it.
How do I extract emails and URLs from text?
Use Extract from Text and select emails or URLs as the value type. Review the matches, apply deduplication or sorting if appropriate, and export the result as TXT or CSV.
Can I convert Markdown to PDF?
Yes. Markdown to PDF accepts non-empty UTF-8 Markdown files with .md or .markdown extensions and supports headings, lists, tables, code, links, safely referenced or embedded images under the tool’s resource policy, Unicode, and Arabic.
Is Text to ASCII an image converter?
No. Text to ASCII generates text-based ASCII art from text. It does not convert an image into ASCII art.
Which tool should I start with?
Start with the task: Word Counter for measurement, Text Statistics for analysis, List Cleaner for line-based cleanup, Text Diff Checker for revisions, Hidden Text Detector for invisible characters, Extract from Text for pattern collection, Case Converter for capitalization, Text to ASCII for decorative text, and Markdown to PDF for document output.
Conclusion
The right text tool can turn a repetitive manual task into a short, checkable workflow. Measure with a word counter, analyze patterns with text statistics, clean entries with a list cleaner, compare versions with a diff checker, and inspect invisible characters when ordinary text behaves strangely.
For structured work, extract values before organizing them, and verify transformed output against the original. For developer tasks, treat whitespace, case, punctuation, and Unicode as potentially significant. For documents, review the final PDF rather than assuming the Markdown source tells the whole story.
When you know the task but not the tool, start with the Text Tools library and choose the focused utility that matches the result you need.