CONTENT CREATION

Nightly Back-Translation Drift Digest to Slack

Runs every night against the main branch, back-translates the strings changed in the last 24 hours.

CategoryContent Creation
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionCollect strings changed in last 24h on mainGitHubGitHub
  • ActionBack-translate changed strings to sourceOpenAI
  • LogicKeep only entries above drift threshold
  • OutputPost drift digest to loc-team Slack channelSlack

What it does

On a nightly schedule it finds the translated strings that changed in the past day, back-translates each to the source language, and posts a concise Slack digest summarizing how many strings shipped, how many drifted, and the specific entries that need a human look.

When to use it

Use it when localization changes land continuously and you want a low-friction daily heartbeat instead of blocking every PR. It keeps the loc team aware of accumulating drift without anyone manually diffing catalogs each morning.

How it works

  1. 1A nightly schedule fires (e.g. 6am in the team's timezone).
  2. 2The flow queries GitHub for commits to the default branch in the last 24 hours that touched locale files and collects the changed target strings.
  3. 3Each changed string is back-translated to the source language by the LLM.
  4. 4A logic step compares against the source and keeps only entries that exceed the drift threshold.
  5. 5If any drift is found, a formatted digest is posted to the loc-team Slack channel with counts and a bulleted list of strings to review; a clean run posts a short all-clear.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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