Text Tools

Transform and manipulate text strings in your workflows.

Overview

The Text Tools connector is a built-in utility for everyday string operations inside a workflow: trim, case conversion, splitting and joining, replacement, slugification, padding, truncation, and the small inspection helpers (contains, starts-with, ends-with, length).

It complements Regex Tools (pattern-based work) and the AI Transform node (natural-language reshaping). Use Text Tools when the operation is a single deterministic transform on a known string - normalizing customer-supplied input before a database insert, generating URL slugs from product names, or trimming and casing values pulled from a CSV.

What You Can Do

The Text connector exposes these tools:

• case - Convert to upper, lower, title, sentence, camel, or snake case.
• trim - Strip leading and trailing whitespace.
• pad - Pad a string to a target length on the left, right, or both sides.
• truncate - Shorten a string to a maximum length, optionally with an ellipsis.
• repeat - Repeat a string N times.
• reverse - Reverse the characters in a string.
• slugify - Produce a URL-safe slug from arbitrary text.
• split - Split a string on a literal separator into an array.
• join - Join an array of strings with a separator.
• replace - Replace occurrences of a literal substring.
• substring - Extract a range of characters by index.
• contains - True/false check for a literal substring.
• starts-with - True/false check for a literal prefix.
• ends-with - True/false check for a literal suffix.
• count-chars - Count characters in a string.
• count-words - Count whitespace-separated words.

Authentication and Setup

No connection or authentication is required. These tools are built into the platform and available in every workflow by default - just drop a Connector node onto the canvas and pick the tool you need.

Using in a Workflow

Add a Connector node, select Text Tools, and pick a mode:

• Direct Mode - The default. These are simple deterministic operations, so call them directly.
• Agent Mode - Rarely useful; if you need an AI to decide which transform to apply, use a Transform node instead.

For pattern-based work (extracting an order ID, matching a SKU shape) use Regex Tools. For free-form rewrites (paraphrase, translate, summarize) use the AI Transform node.

Tips

• Normalize at the boundary - run trim and a case step on user-supplied fields as soon as they enter the workflow, so downstream comparisons work.
• Use slugify for URL paths and file names - it handles unicode, spaces, and punctuation consistently.
• Truncate with care - downstream systems often have field length limits (Klaviyo profile fields, NetSuite memo lines). Apply truncate just before the write.
• Use contains in a Condition node rather than a Transform with custom logic for simple presence checks.

Common Pitfalls

• Case-sensitive comparisons - contains, starts-with, and ends-with match exactly. Lowercase both sides first if you want case-insensitive behavior.
• Whitespace is not always ASCII - Non-breaking spaces and zero-width characters survive trim. Strip them explicitly with replace if they're a problem.
• Character vs byte counts - count-chars counts code points. Multi-byte characters (emoji, CJK) take more bytes than chars when stored.
• Slugify is lossy - It strips diacritics and punctuation. Don't use it as the only identifier for a record.

Common Use Cases

• Use AI to Clean and Normalize Messy Data
• Validate and Clean CSV Data Before Import
• Auto-Tag and Enrich Product Data Using AI
• Build an ETL Pipeline with CSV, Transform, and MySQL
• Send Personalized Order Confirmation Emails

Related Articles

• Adding a New Connection
• Regex Tools
• Validation Tools
• JSON Tools
• Encoding Tools

For technical API details and field specifications, see the Text Tools documentation.