DOCUMENT OPS

Triage Figma handoff comments into Coda dev tasks with AI

On a schedule, this workflow reads unresolved comments on handoff-ready Figma frames, uses AI to classify each as a blocker, question, or nice-to-have, and creates prioritized…

CategoryDocument Ops
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled triage run
  • ActionFetch unresolved handoff comments from FigmaFigmaFigma
  • ActionClassify comments by severity with AIOpenAI
  • LogicRoute blockers and questions, log nice-to-haves
  • ActionCreate prioritized dev task rows in CodaCodaCoda
  • OutputReturn created-task summaryCodaCoda

What it does

Keeps design feedback from getting buried in Figma threads. It collects unresolved comments on frames already in handoff, uses AI to judge whether each is a blocking issue, an open question, or a minor polish note, and turns the actionable ones into prioritized Coda tasks.

When to use it

Use it when handoff comments pile up in Figma and engineers never see the ones that actually block the build. Good for teams that run their dev queue in Coda and want feedback routed there automatically with a sensible priority.

How it works

  1. 1A schedule runs the triage at a set interval.
  2. 2The workflow fetches unresolved comments on frames currently marked for handoff in Figma.
  3. 3OpenAI classifies each comment as blocker, question, or nice-to-have and writes a short summary.
  4. 4A logic branch drops noise and routes blockers and questions to the task table while logging nice-to-haves.
  5. 5It creates a Coda dev task row for each actionable comment with priority and a deep link back to the Figma thread.
  6. 6A summary of created tasks is returned.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FigmaFiles, frames, comments, assets.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect CodaDocs, packs, 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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