CONTENT CREATION

Localize product-page variants from a Coda spec into a GitHub review PR

Reads a master product-page spec from Coda, generates localized copy variants for each target locale.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled or manual run pulls master spec rowCodaCoda
  • LogicKeep only locales flagged needs-update
  • ActionGenerate localized copy per locale with OpenAIOpenAI
  • ActionWrite each variant to its locale path in the repoGitHubGitHub
  • OutputOpen one review PR and link it back on the Coda rowGitHubGitHub

What it does

Turns one canonical product-page spec in Coda into per-locale page variants and bundles them into a review-ready GitHub pull request. Nothing publishes automatically — a human approves the PR.

When to use it

When marketing maintains a single source-of-truth page spec and needs the same page in several languages without copy-pasting into a translation tool and hand-committing files. Run it whenever the master row in Coda is marked ready.

How it works

  1. 1A scheduled check (or manual run) pulls the master spec row from Coda, including the locale list and tone notes.
  2. 2A filter keeps only locales flagged "needs update" so settled translations are not regenerated.
  3. 3For each remaining locale, OpenAI rewrites the headline, body, and CTA in-language with the brand tone, preserving the page structure.
  4. 4Each variant is written to its locale path in the repo (e.g. `pages/de/product.mdx`).
  5. 5The flow opens one GitHub PR collecting all variants, labeled for the localization reviewers, and posts the PR link back onto the Coda row.

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 GitHubRepos, issues, pull requests, actions.
  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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