DOCUMENT OPS

Gate a Figma handoff on spec completeness before publishing to Dropbox

On a handoff request this audits the Figma frame for missing annotations, unnamed layers, and detached components.

CategoryDocument Ops
Enginesim
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHandoff request webhook with frame URLHTTP webhook
  • ActionFetch frame node tree and metadataFigmaFigma
  • LogicRun completeness checks and branch pass/fail
  • ActionOn fail: send punch list to designer in SlackSlack
  • ActionOn pass: render frame export and specFigmaFigma
  • OutputPublish passing packet to /ready in DropboxDropboxDropbox

What it does

Acts as a quality gate between design and engineering. It inspects a Figma frame for the things that break a handoff — unnamed layers, detached components, missing redline annotations — and only lets a frame through to Dropbox once it passes, routing failures back to the designer with a specific punch list.

When to use it

Use it when engineering keeps receiving incomplete specs and you want to enforce a consistent definition-of-ready before any packet lands in the shared Dropbox handoff folder.

How it works

  1. 1A designer triggers a handoff request via webhook with the frame URL.
  2. 2The flow pulls the frame's full node tree and metadata from Figma.
  3. 3It runs completeness checks: layer naming, component attachment, annotation presence.
  4. 4A branch decides pass or fail based on the check results.
  5. 5If it fails, a Slack message goes to the designer listing each missing item.
  6. 6If it passes, the rendered export and spec are published to the `/ready` folder in Dropbox.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FigmaFiles, frames, comments, assets.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect DropboxFiles and folders.
  4. 4
    Connect HTTP webhookTrigger any URL on agent actions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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