CONTENT CREATION
Pre-Release Localization Back-Translation Report to Notion
When a release branch is cut, back-translates all shipped UI strings across every locale and publishes a Notion page ranking the highest-risk meaning drifts so reviewers can sign…
How it runs
The automated pipeline, trigger to output.
- TriggerRelease branch pushed (release/*)GitHub
- ActionRead full locale catalog from the branchGitHub
- ActionBack-translate all target strings to sourceOpenAI
- LogicRank by drift severity and classify issue types
- OutputPublish ranked drift report to Notion release-QA DBNotion
What it does
At release-cut time it sweeps the entire localized string catalog, back-translates each target string to the source language, and assembles a structured Notion report grouped by locale and severity, giving the release manager a single page to review drift before approving the ship.
When to use it
Use this on a per-release cadence rather than per-PR when you want one consolidated localization sign-off artifact instead of inline checks. Good for teams with formal release reviews and many locales where a full-catalog audit at the gate is worth the cost.
How it works
- 1A new release branch matching your pattern (e.g. `release/*`) is pushed, triggering the flow.
- 2The flow reads the full set of locale files from that branch via GitHub.
- 3Every target string is back-translated to the source language by the LLM in batches.
- 4A scoring step ranks each string by drift severity and tags likely issue types (negation loss, tone shift, truncated meaning).
- 5The findings are written to a new Notion page under your release-QA database, formatted as a sortable table with the worst offenders at the top for reviewer sign-off.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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