CONTENT CREATION
GitHub release tag to branded changelog hero art in Notion
When you publish a GitHub release, this generates an on-brand hero graphic for the changelog entry, runs an automated brand-compliance check.
How it runs
The automated pipeline, trigger to output.
- TriggerGitHub release published webhookGitHub
- ActionSummarize release notes into a visual concept + headlineOpenAI
- ActionGenerate 16:9 brand hero image from the conceptImage generation
- LogicBrand-compliance check; regenerate once on failure
- ActionUpload approved image to S3 for a stable URLAWS S3
- OutputCreate changelog entry with hero art in NotionNotion
What it does
Turns every published GitHub release into a finished changelog entry: it drafts a hero image prompt from the release notes, generates the art, verifies the result against your brand rules, and files it in Notion ready to publish.
When to use it
Use it if your team cuts releases on GitHub and maintains a customer-facing changelog in Notion. It removes the manual step of briefing a designer or hunting for header art for every version bump.
How it works
- 1A GitHub `release.published` webhook fires with the tag name and release body.
- 2An action summarizes the release body into a short visual concept and headline.
- 3generate-image produces a 16:9 hero graphic using your brand palette and the concept.
- 4A logic step scores the image for brand compliance (logo safe-zone, approved colors, no off-brand text) and routes failures back to regenerate once.
- 5The approved image is uploaded to cloud storage to get a stable URL.
- 6A Notion page is created in the changelog database with the version, notes, and embedded hero image.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect Image generationManaged Nano Banana image renders, metered per image.
- 3Connect AWS S3Buckets, objects, signed URLs.
- 4Connect NotionPages, databases, comments.
- 5Connect OpenAIModels, embeddings, files.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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