> For the complete documentation index, see [llms.txt](https://docs.pletor.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pletor.ai/build-agents/nodes/logic-nodes/split-text-and-list-selector.md). # Split text & List Selector ### Split text The Split node takes one text input and breaks it into distinct parts based on a delimiter you define. Each segment then flows through downstream nodes individually. ### List node Display and select from multiple items to create workflow branches. The List node receives multiple text items and presents them as a selectable list. You manually choose which item to process further, giving you control over workflow direction without regenerating content. ### When to use them * **Batch image/video generation**: Split a single AI Text output (e.g., brief) containing multiple prompts into separate prompts, each feeding its own image or video generation node. * **Variation/branch workflows**: Generate multiple prompts once, then branch into separate generation paths based on your selections. For example, run the same base concept through multiple creative directions at once. * **Processing structured content**: Break apart lists, CSV data, or any formatted text into individual items. ### How to use them {% embed url="" %} You can have a look at [this template agent](https://api.pletor.ai/s/f4b54615-b7f3-444e-a7be-34f5a9e32534) to start building with these nodes. ### When to use List vs. Human Review node * **List node**: Choose between multiple different text options generated in the same run. * **Control node**: Pause to review and/or edit/refine output(s) before continuing. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.pletor.ai/build-agents/nodes/logic-nodes/split-text-and-list-selector.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.