CONTENT CREATION

Notion blog draft to localized multi-format asset pack

Watches a Notion database for posts marked Ready, then turns each long-form draft into a localized pack: social captions per platform, an email teaser, a hero image.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNotion post status set to ReadyNotionNotion
  • ActionFetch full draft bodyNotionNotion
  • ActionGenerate localized captions, email teaser, and meta copyOpenAI
  • ActionGenerate matching hero imageImage generation
  • LogicVerify all locales and formats returned
  • OutputWrite asset pack back to Notion pageNotionNotion

What it does

When a blog draft in Notion is flagged Ready, this workflow expands it into a full repurposing pack in your target locales — short and long social captions, an email teaser, SEO meta description, and a generated hero image — and writes all of it back onto the source page so a human can review before publishing.

When to use it

You maintain an editorial pipeline in Notion and want every approved draft to arrive at review with its derivative assets already drafted and translated, instead of hand-crafting each format and language.

How it works

  1. 1A Notion database row changes status to Ready, firing the trigger.
  2. 2The full page body is fetched from Notion.
  3. 3An OpenAI step rewrites the draft into per-locale variants: platform captions, an email teaser, and meta copy.
  4. 4A generate-image step produces a hero image matching the post's topic.
  5. 5A logic step checks that every required locale and format came back non-empty.
  6. 6The assets and image are written back to the Notion page as new blocks and properties for editor review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Image generationManaged Nano Banana image renders, metered per image.
  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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