CONTENT CREATION

Generate redacted annotated screenshots from a Monday request

When a Monday item is moved to Ready for Annotation, blurs sensitive regions, adds callouts in Figma, and attaches the finished redacted image set back to the Monday item.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonday item moved to Ready for Annotationmonday.com
  • ActionDownload raw attachments and read redaction boxesmonday.com
  • ActionBlur regions and annotate with callouts in FigmaFigmaFigma
  • LogicVerify all requested redactions were applied
  • OutputAttach redacted set to Monday item and mark Donemonday.com

What it does

Drives screenshot annotation off your Monday board. When someone moves a request item to the Ready for Annotation status, the workflow grabs the attached raw captures, blurs the PII or customer-data regions specified on the item, annotates them with callouts in Figma, and posts the finished redacted images back onto the same Monday item as attachments.

When to use it

Use it when support or docs requests come in through Monday and the screenshots contain account numbers, emails, or other data that must be masked before publishing. It keeps the request, the redaction, and the deliverable in one place.

How it works

  1. 1A status change to Ready for Annotation on the Monday board fires the trigger.
  2. 2The flow downloads the raw image attachments and reads the redaction rectangles from the item's column values.
  3. 3It applies blur to those regions, then places each image into the Figma callout template and exports annotated PNGs.
  4. 4A logic check verifies every requested redaction box was applied before continuing.
  5. 5The finished images are attached back to the Monday item and its status is set to Done.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect monday.comVisual work management for teams.
  2. 2
    Connect FigmaFiles, frames, comments, assets.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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