CONTENT CREATION

Agent triages stale screens, recaptures, and rewrites doc captions

An agent reviews a route-change diff, decides which screenshots are genuinely affected, recaptures them, rewrites the surrounding doc captions to match the new UI.

CategoryContent Creation
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPush to main with changed filesGitHubGitHub
  • ActionAgent judges which documented screens are affectedOpenAI
  • ActionCapture fresh screenshots for affected screensBrowserbase
  • ActionAgent rewrites captions and alt text to matchOpenAI
  • OutputOpen a review-ready PR with images and copyGitHubGitHub

What it does

Goes beyond mechanical recapture: an agent reads the code diff and existing doc prose, judges which documented screens actually changed meaningfully, recaptures those, and updates the captions and alt text so the words match the new picture — then bundles it all into one PR.

When to use it

Your docs have descriptive captions that go wrong when the UI moves, and naive screenshot replacement leaves the text lying. You want a human-quality refresh, reviewed in one diff.

How it works

  1. 1A push to main triggers the agent with the changed files.
  2. 2The agent inspects the route diff and the current doc pages to decide which screens are materially affected.
  3. 3For each, Browserbase captures a fresh screenshot.
  4. 4The agent rewrites the affected captions and image alt text to describe the new UI accurately.
  5. 5It commits images and prose together.
  6. 6A pull request opens summarizing what changed visually and in copy, for human review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect BrowserbaseHeadless browsers, sessions, replays.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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