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Text GenerationAvailable on paid plans

Gemini Text Generator

Generate text with Gemini 3.5 Flash-Lite, 3.1 Pro Preview, or 3.8 Flash using structured output, search grounding, URL context, code execution, and thinking controls

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Inputs

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Execution Steps

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Overview

Gemini Text Generator turns a prompt into text with your choice of Gemini 3.5 Flash-Lite, 3.1 Pro Preview, or 3.8 Flash, plus optional system instructions, structured JSON, search grounding, URL context, code execution, and thinking controls. Use it for copy drafts, transformations, ideation, summarization, and structured text outputs.

Use cases

  • Draft campaign copy, social captions, email variants, or positioning notes from a clear brief.
  • Transform raw notes into summaries, outlines, FAQs, or JSON-shaped outputs for downstream work.
  • Use search, URL context, or code execution when the prompt needs fresh sources, page context, or calculations.

Input tips

  • Put the main task in contents and use system_instruction only for durable tone, role, or format guidance.
  • Choose Gemini 3.5 Flash-Lite, 3.1 Pro Preview, or 3.8 Flash in Advanced Settings. Flash-Lite is the default.
  • Use max_output_tokens only when you need to constrain response length.
  • Provide response_json_schema when the answer must be valid JSON; keep the schema concise.
  • Turn on Google Search, URL context, or code execution only when those tools are needed.

Expected output

The AI Tool returns generated text, the model ID used, optional finish reason, usage stats for prompt, completion, total, and cached tokens, plus cost metadata. The web view renders Markdown, lets users switch to raw text, copy the output, expand fullscreen, and inspect token usage.

Caveats

  • Review generated copy before publishing; the AI Tool does not guarantee factual accuracy or brand approval.
  • Search-grounded or URL-context outputs still need source review, especially for public claims.
  • Invalid JSON schema may be ignored; structured output can conflict with some grounding modes.
  • High thinking, tool use, or long max output settings can increase latency and token use.
  • Token limits and finish reasons can affect completeness.

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