CONTENT CREATION

Agent-run translation QA gate for localized asset packs

An agent reviews each machine-translated asset variant against the source draft for meaning drift and tone, fixes safe issues automatically.

CategoryContent Creation
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew asset pack added in NotionNotionNotion
  • ActionFetch source draft and localized variantsNotionNotion
  • LogicAgent scores variants and splits clean vs risky
  • ActionMark clean and auto-fixed variants approvedNotionNotion
  • OutputEscalate risky variants to Slack reviewerSlack

What it does

When a localized asset pack is generated, an agent reads each translated variant alongside the original draft, judges whether the translation preserved meaning, brand tone, and any do-not-translate terms, auto-corrects low-risk problems, and escalates ambiguous or high-stakes cases to a human reviewer in Slack with its reasoning attached.

When to use it

You ship content in regulated or brand-sensitive markets where raw machine translation isn't trustworthy enough to publish, and you want an automated reviewer that only interrupts a human when judgment is genuinely required.

How it works

  1. 1A new asset pack lands in the Notion database, firing the trigger.
  2. 2The agent fetches both the source draft and every localized variant.
  3. 3The agent evaluates each variant for meaning drift, tone, and protected terms.
  4. 4A logic branch separates clean and auto-fixable variants from risky ones.
  5. 5Clean and auto-corrected variants are written back to Notion as approved.
  6. 6Risky variants are routed to Slack with the agent's findings for human sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  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.

Run this workflow in your colony.

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