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Placeholder Dialogue Generator

Used by developers, writers, and creators worldwide.

A placeholder dialogue generator solves a specific, annoying problem: every chat UI mockup, messaging prototype, or screenplay draft needs believable conversation text, and lorem ipsum breaks the illusion immediately. This tool produces two-character exchanges across four settings — casual, professional, customer support, and romantic — with randomized name pairs so repeated outputs don't look identical. Set the number of lines to match your container. Six lines fills a standard mobile chat frame; twelve or more stress-tests a scrollable thread. The four settings do distinct work: casual for consumer apps, professional for B2B demos, support for helpdesk UIs, romantic for dating apps or narrative games. Copy output straight into Figma text layers, a screenplay formatter, or a seed script.

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How to use

  1. Choose your options above
  2. Click Generate
  3. Copy your result

Detailed instructions

  1. Select a setting from the dropdown that matches your project context: casual, professional, customer support, or romantic.
  2. Set the number of lines using the number input — use 6 for a standard screen fill, or higher to test scrollable layouts.
  3. Click the generate button to produce a fresh two-character conversation with randomized names.
  4. Copy the output text and paste it directly into your design tool, screenplay formatter, or code editor.
  5. Click generate again without changing settings to get a new name pair and different line content for additional screens.

Use Cases

  • •Populating Figma chat bubble components with varied text to expose overflow and truncation issues
  • •Seeding a development database with realistic sender/message pairs instead of 'test message 1' strings
  • •Filling a helpdesk UI demo with customer support dialogue before a stakeholder walkthrough
  • •Blocking scene rhythm in Final Draft or Fade In before writing real character lines
  • •Generating onboarding screen copy for a dating app prototype in Storybook

Tips

  • →Generate multiple outputs at the same setting and line count to build a library of varied chat screens — different name pairs prevent visual repetition across mockup frames.
  • →Use customer support setting when demoing helpdesk or ticketing software; the structured request-and-response pattern looks far more authentic than casual banter in that context.
  • →For mobile chat UI testing, generate at 4 lines and 12 lines separately — the short version tests empty-state designs, the long version tests scroll behavior and timestamp placement.
  • →In screenplay work, use the output as a structural skeleton: keep the line count and emotional rhythm, but rewrite the actual words to fit your characters and story.
  • →Paste several outputs into a single Figma frame before swapping in real copy — mismatched text lengths expose padding and bubble sizing issues early, before the content is finalized.
  • →Combine the romantic setting with a low line count (4) for dating app match-screen previews, where only the opening exchange needs to be visible.

FAQ

how do I use placeholder dialogue in a Figma chat mockup

Generate a conversation at your target line count, then paste each line into individual chat bubble text layers. Alternate speakers map naturally to left and right alignment. Run two or three generations to get varied text lengths — this catches overflow and truncation that uniform lorem ipsum misses entirely.

what's the difference between the four dialogue settings

Casual produces short, informal exchanges with contractions and everyday topics — good for consumer messaging apps. Professional generates workplace-appropriate phrasing for B2B demos. Customer support outputs structured request-and-resolution patterns for helpdesk UIs. Romantic produces warmer, more personal exchanges suited to dating apps or interactive fiction.

can I parse the output to seed a test database with chat records

Yes. Each line follows a 'Name: message' format, so splitting on the first colon gives you clean sender and message fields. That makes it straightforward to insert records into a Postgres or SQLite dev database without hand-writing repetitive test strings.