CONTENT CREATION

Split a master doc into per-locale translation tasks with glossary

When a master content doc is finalized in Coda, this fans it out into one Linear translation task per target locale.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCoda doc marked Ready for translationCodaCoda
  • ActionRead master doc, locales, and glossary tablesCodaCoda
  • LogicSkip locale rows missing target or due date
  • ActionBuild per-locale brief with relevant glossary termsOpenAI
  • ActionCreate one Linear task per localeLinearLinear
  • OutputWrite issue links back to Coda trackerCodaCoda

What it does

Turns a single approved master document into a clean translation handoff packet. It reads the finalized doc, extracts the locale list and glossary table, then opens a tracked Linear task per locale with the source copy, locale-specific glossary terms, and a deadline pre-filled.

When to use it

Run this the moment a source doc is signed off and you need it translated into several languages. It replaces the manual copy-paste-into-tickets ritual and guarantees every translator gets the same glossary and instructions.

How it works

  1. 1A Coda button or status flip to "Ready for translation" fires the trigger.
  2. 2The flow reads the master doc body plus the locales and glossary tables from Coda.
  3. 3A branch checks each row has a target locale and at least one due date; rows missing data are skipped and flagged.
  4. 4For each valid locale, OpenAI assembles a per-locale brief that pairs the source text with only the glossary terms relevant to that language.
  5. 5A Linear issue is created per locale in the Localization project, titled by locale, with the brief in the description and the due date set.
  6. 6The final step writes the issue links back into the Coda tracking table so the master doc shows live status.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CodaDocs, packs, automations.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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