CONTENT CREATION

Audit glossary drift across locales before opening translation tasks

On a schedule, compares each locale's existing glossary against the canonical master glossary in Coda, flags terms that are missing, stale, or conflicting, and files a Linear…

CategoryContent Creation
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly glossary audit schedule
  • ActionRead master and per-locale glossariesCodaCoda
  • ActionDiff and classify term drift per localeOpenAI
  • LogicSkip locales with no drift
  • ActionFile Linear cleanup task per affected localeLinearLinear
  • OutputSend drift digest to the teamSlack

What it does

Keeps translation glossaries honest. It pulls the canonical glossary plus every locale's working glossary, diffs them, and surfaces terms that are missing, outdated, or translated inconsistently, so drift is fixed before it contaminates the next batch of content.

When to use it

Run this weekly, or right before a big content push, when you suspect locale glossaries have diverged from the master and you want a clean baseline before fanning out new translation tasks.

How it works

  1. 1A weekly schedule kicks off the audit.
  2. 2The flow reads the master glossary and each per-locale glossary from Coda.
  3. 3OpenAI compares the sets and classifies each term as missing, stale, or conflicting with the canonical entry.
  4. 4A branch decides per locale: if zero issues, skip; otherwise continue.
  5. 5For each locale with drift, a Linear cleanup task is opened listing the exact terms to reconcile.
  6. 6A digest of the drift summary across all locales is delivered so the team sees the overall health at a glance.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CodaDocs, packs, automations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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