RegexReplace

DataTools

Security Level 2 - Write

SindByte tool execution flow: voice command, AI parse, execute, validate, result

Description

The most powerful text transformation! RegexReplace replaces complex patterns using regular expressions - remove HTML tags, convert date formats, normalize IDs, clean up whitespace and much more. Impossible replacements become child's play!

With capture group references ($1, $2, ...), callback functions and comprehensive regex options, you transform text with unlimited flexibility. A single command replaces hours of manual work!

Why This Tool Stands Out

Complex Transformations with one command
Remove HTML Tags automatic
Capture References - $1, $2, etc.
Flexible Formatting of any data

Perfect for:

Web developers, data engineers, content managers and everyone who needs to perform complex text transformations. Ideal for HTML cleanup, data migrations, format normalization, log processing and code refactoring. Perfect for CMS imports, API data preprocessing, report generation and text analytics!

Workflow support; time savings depend on the task

Instead of performing complex replacements manually, writing scripts or configuring tools, RegexReplace handles the most demanding transformations in seconds - with referential integrity and 100% consistency!

JSON Parameters

text REQUIRED (String)The text to perform the replacement in.
pattern REQUIRED (String)The regex pattern to find.
replacement REQUIRED (String)The replacement text. Can contain capture group references ($1, $2, etc.).
replaceAll OPTIONAL (Boolean)Whether all occurrences should be replaced. Default: true
caseSensitive OPTIONAL (Boolean)Whether the search should be case-sensitive. Default: false

Example Call

{
  "tool": "RegexReplace",
  "params": {
    "text": "<p>Hello World</p><br><div>Test</div>",
    "pattern": "<[^>]+>",
    "replacement": "",
    "replaceAll": true,
    "caseSensitive": false
  }
}

Example Usage

Prepare the Source Text

Load the text to transform - e.g. HTML, logs or unstructured data.

Define the Regex Pattern

Create a regular expression pattern that identifies the parts to replace.

Use the Result

Use the transformed text for your application, database or API.

Return Values

The tool returns an object with the following properties:

result (String)
The text after the regex replacement
replacementsMade (Integer)
Number of replacements performed
pattern (String)
The regex pattern used
originalLength (Integer)
Length of the original text
newLength (Integer)
Length of the resulting text
error (String, optional)
Error message if the operation failed

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