Kebab Case Converter

Tool Overview

This kebab case converter transforms any text into kebab-case, the lowercase, hyphen-separated style often used in CSS class names, HTML attributes, URL slugs and configuration keys. You can paste text in almost any format, including plain phrases, snake_case, camelCase or PascalCase, and the tool will produce a clean kebab-case output such as "my-variable-name" or "css-class-name".

The problem it solves is consistent, predictable naming. When you work across multiple tools, frameworks and teams, inconsistent naming styles lead to confusion and bugs. Manually converting text to kebab-case is error prone, especially when dealing with mixed case, underscores, spaces, punctuation and non-ASCII characters. This tool automates those decisions, applies a precise sequence of transformations and shows which rules were applied.

The interface is built for both developers and non-technical users. The main converter panel shows input and output side by side, a settings panel lets you customize delimiters and behavior, a history panel records past conversions and a dedicated AI enhancer can refine raw titles into SEO-friendly, concise kebab-case slugs.

Background & Concept Explanation

Kebab-case is a naming style where all letters are lowercase and words are separated by hyphens or another delimiter. For example, "My Cool Project" becomes "my-cool-project". In many systems, kebab-case is easier to read than concatenated words and more URL-friendly than names with spaces or underscores. In CSS, class and id names are often written in kebab-case; in URLs, hyphen-separated slugs are common for improving readability and search engine clarity.

However, source text rarely arrives in perfect shape. Some text may be in camelCase ("myCoolProject"), PascalCase ("MyCoolProject"), snake_case ("my_cool_project") or include symbols, accented characters and mixed whitespace. A good converter must be able to detect boundaries between words, normalize separators and remove or adapt characters that are unsafe in CSS, HTML or URLs. A related operation involves converting to snake_case as part of a similar workflow.

This kebab-case converter applies a consistent set of rules to transform messy input into a safe identifier. It splits camelCase into words, replaces spaces, underscores, dots and hyphens with a single chosen delimiter, removes unsupported symbols and normalizes accented characters. It then applies casing rules, either forcing everything to lowercase or preserving the original case if you ask it to.

The tool also supports bulk mode, where each line of input is treated as a separate item, and outputs one converted line per input line. This is useful when you need to convert a list of names or labels at once. A rule insights panel lists which transformation steps were applied, providing transparency for users who want to understand exactly how their input was changed.

Key Features

• Automatic camelCase and PascalCase splitting – When the tool detects lowercase letters followed by uppercase letters, it inserts the chosen delimiter between them. For example, "myCoolProject" becomes "my-cool-project". This step helps convert variable-like tokens into proper kebab-case words.
• Whitespace and separator normalization – The converter replaces runs of whitespace, underscores, hyphens and dots with a single delimiter. This means "My cool_project.name" becomes "my-cool-project-name" (or an equivalent using your chosen delimiter), eliminating inconsistent separators.
• Special character removal – To keep the output safe for CSS, HTML and URLs, the tool removes characters that are not alphanumeric or the chosen delimiter. It does this using a regular expression that allows numbers, letters and the delimiter while stripping everything else.
• Unicode normalization – For characters outside the basic ASCII range, the converter applies a simple Unicode normalization step. It uses a decomposition form and removes combining marks, which turns many accented characters into their base Latin equivalents. This reduces the risk of unexpected behavior in systems that are not fully Unicode-aware.
• Configurable delimiter – By default, the delimiter is a hyphen, but you can choose other delimiters such as an underscore, dot or forward slash. The settings panel lets you pick from a small set of supported delimiters, and all normalization rules will use that delimiter.
• Lowercase or preserve case mode – In most kebab-case naming conventions, all letters are lowercase. The converter enforces this by default. If you enable the preserve case setting, it will skip the final lowercase step and keep the original letter casing, while still applying all other transformations.
• Bulk processing mode – When bulk mode is enabled, the converter treats each line of the input as a separate string. It converts each line individually and then joins the results with newline characters. This is ideal for processing lists of labels or names quickly.
• History tracking – The tool maintains a local history of past conversions in the browser. It saves input, output, a generated id and a timestamp for each item. Duplicate outputs are filtered out so that history remains concise, and it is persisted in local storage so it survives page reloads.
• Rule insights visualization – After each conversion, the tool collects rule insights describing which transformations were applied, such as "Split CamelCase boundaries", "Normalized spaces and separators", "Removed special characters" or "Normalized unicode characters". A panel displays these insights as colored chips.
• Copy-to-clipboard and auto-copy support – With one click, you can copy the converted output to the clipboard. Internally, the converter uses a safe clipboard API and returns success status. When used in combination with the optional auto-copy setting, the output can be copied automatically as part of your workflow.
• Optional AI enhancer – The AI enhancer is an optional area that calls an external AI service to refine your input text into an SEO-friendly, concise kebab-case slug. It is off by default and only runs when you explicitly click the enhancement button, keeping the core conversion deterministic.

Common Use Cases

Front-end developers use the kebab case converter to generate consistent CSS class names and HTML id attributes from human-readable labels or design specs. For example, a heading like "Primary Button Large" can be converted to "primary-button-large" for use in stylesheets and templates.

Backend developers and DevOps engineers use the tool when creating configuration keys, environment variable names or command-line flags where a hyphenated lowercase style is preferred. The converter turns descriptive phrases and mixed-case identifiers into stable kebab-case keys. For adjacent tasks, converting to camelCase addresses a complementary step.

Content and SEO specialists use it to build URL slugs from article titles. A title such as "10 Tips for Better Site Performance!" can become "10-tips-for-better-site-performance", ready to be used in path segments while avoiding unsafe characters.

Teams on shared projects use history and bulk mode to ensure that naming is consistent across files and modules. By converting lists of sections or components in one go, they can avoid subtle typos or mismatched naming schemes.

People working with design systems and component libraries use the tool to translate design tokens and component names into a format suitable for code, CSS and documentation. Combining custom delimiters and preserve case settings can help integrate different naming standards.

How to Use This Tool (Step-by-Step)

1. Open the converter and locate the main input area on the left. This is where you can either type text directly or paste content from another source, such as a design specification, document or existing code.
2. In the settings panel, choose your preferred delimiter and options. Leave the delimiter as "-" for standard kebab-case, or switch to "_", "." or "/" if you need a different style. Decide whether you want bulk mode for line-by-line processing and whether you want to preserve the original case.
3. Type or paste your input text into the input field. If bulk mode is off, the entire text is treated as one string. If bulk mode is on, each line is treated as a separate string to convert, and the output will contain a corresponding line for each input line.
4. As you enter or change text, the converter automatically applies the kebab-case transformation. The resulting kebab-case string (or strings) appears in the output area on the right, styled using your chosen delimiter and casing option.
5. Review the output and the rule insights panel. The rule chips will tell you which transformations were applied, such as splitting camelCase, normalizing whitespace, removing symbols or normalizing Unicode. This helps you verify that the converter performed the expected operations.
6. If you want to reuse a previous conversion, open the history panel. Click on any history item to load its input back into the converter. The displayed output will update accordingly, and you can adjust settings or text if needed.
7. When you are satisfied with the result, click the "Copy Output" button. The tool attempts to copy the output to your clipboard and shows a brief confirmation state when successful.
8. If you want extra optimization for a slug, scroll to the optional AI refinement area and click the enhancement button. The tool sends your raw input to the AI service, which returns a refined, concise kebab-case suggestion. The enhancer then updates the input text with this refined version so you can re-run the standard conversion if needed.
9. Use the clear and history controls to reset your work as needed. You can clear the history to remove old items or adjust settings to switch between bulk and single-line mode for different tasks.

Calculations & Logic

The core kebab-case logic is contained in a function that accepts an input string and a settings object. It first checks whether the trimmed input is empty; if so, it returns an empty output and no rules. Otherwise, it initializes an empty rules list and begins transforming the text. When working with related formats, converting to PascalCase can be a useful part of the process.

To detect camelCase or PascalCase boundaries, it uses a regular expression that matches a lowercase or digit followed by an uppercase letter. When such a pair is found, it inserts the delimiter (surrounded by spaces for clarity during intermediate processing) between the characters and records a "Split CamelCase boundaries" rule.

Next, it normalizes whitespace and existing delimiters. A pattern matching sequences of whitespace, underscores, hyphens or dots is replaced with a single instance of the chosen delimiter. This step ensures that all separators are consistent, whether the input contained spaces, underscores or mixed symbols. A "Normalized spaces and separators" rule is recorded when this happens.

To handle special characters, the function escapes the delimiter for use in a regular expression, then constructs a pattern that allows only letters, numbers and that delimiter. Any other characters are stripped out. If this rule is triggered, a "Removed special characters" rule is added.

For Unicode normalization, the function checks for non-ASCII characters, then uses standard Unicode normalization in NFD form to decompose combined characters into base characters and diacritic marks. It removes diacritic marks using a range of combining code points. When this occurs, a "Normalized unicode characters" rule is added. In some workflows, converting to sentence case is a relevant follow-up operation.

Finally, if the preserve case setting is not enabled, the function converts the entire string to lowercase. If the original input contained uppercase letters, a rule is recorded noting that case was converted. After all transformations, the function trims leading and trailing delimiters using a regular expression built from the escaped delimiter.

The resulting output and the list of unique rules are returned. Before returning, the rules list is deduplicated by serializing each rule to JSON, creating a set, and then parsing each unique entry back to objects. This prevents duplicate rule descriptions when the same type of transformation is applied more than once.

The AI refinement function is separate. It checks that an API key is available and that the input is non-empty. It then calls an AI model with a prompt that asks for an optimized, semantic kebab-case slug, focused on keywords and without filler words. The function returns the trimmed AI response if available, or falls back to the original text if the AI call fails or produces no output.

Tips, Limitations & Best Practices

Use the default hyphen delimiter when you need standard kebab-case for CSS classes, HTML attributes and URLs. Switch to an underscore or dot only when working with systems that explicitly require those separators. For related processing needs, converting to Title Case handles a complementary task.

Be aware that the converter removes special characters, including punctuation and some symbols. If you need to preserve certain characters, consider adjusting your input before running the conversion or manually reintroducing them after conversion.

When working with non-English text that includes many accented characters, remember that the Unicode normalization step may strip accents. This is often desirable for URL slugs and CSS names, but may not be appropriate if you must preserve exact spelling visually.

Bulk mode is powerful for batch operations, but it applies the same settings and transformations to every line. Review a sample line carefully to make sure the rules behave the way you expect before processing very long lists.

Treat AI refinement as an optional helper, especially for SEO. Always review the AI-suggested slugs to make sure they accurately represent your content and respect any naming rules or brand guidelines you must follow.

Keep in mind that some programming languages and environments do not allow hyphens in variable names. Use kebab-case for CSS classes, HTML attributes and URLs as intended, and choose other naming styles such as camelCase or snake_case for variables and function names inside code.