CONTENT CREATION

Render localized screenshot previews on every UI pull request

When a UI PR is opened, generates localized screenshot previews for key markets from the branch's Figma frame and posts them as a comment so reviewers see copy impact before merge.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerUI-labeled pull request opened or updatedGitHubGitHub
  • ActionRead affected frame + representative locale setAirtableAirtable
  • ActionPopulate Figma frame per locale and export previewsFigmaFigma
  • LogicFlag locales where copy overflows node bounds
  • OutputPost renders + overflow warnings as PR commentGitHubGitHub

What it does

Gives reviewers a visual, multi-market preview of how a UI change reads in real languages. When a pull request touches UI, it renders the affected screen in a handful of representative locales and posts them inline on the PR, surfacing truncation and layout breaks during review instead of after release.

When to use it

Use it on repos where copy or layout changes routinely break non-English screens. Catching German overflow or Japanese line-wrap at review time is far cheaper than a hotfix post-launch.

How it works

  1. 1A pull request labeled ui is opened or updated, firing the trigger.
  2. 2The flow reads which frame the PR affects and the representative locale set.
  3. 3It populates the Figma frame with each locale's translated strings and exports preview PNGs.
  4. 4A logic step flags any locale where text exceeds the node bounds.
  5. 5Renders and overflow warnings are posted as a GitHub PR comment for reviewers.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect FigmaFiles, frames, comments, assets.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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