CONTENT CREATION
Mirror a release into your README changelog and an in-app status banner
When a release publishes, formats the notes into your hosted documentation changelog and posts a short in-app status banner to Slack for the team to ship.
How it runs
The automated pipeline, trigger to output.
- TriggerGitHub release publishedGitHub
- ActionFormat docs changelog entry and banner lineOpenAI
- ActionPublish changelog entry to ReadMeReadMe
- OutputPost in-app banner copy to SlackSlack
What it does
This workflow keeps your public docs and in-product messaging current the moment you ship. On a published GitHub release it reads the notes and asks OpenAI to produce two outputs: a properly formatted changelog entry suited to your hosted documentation, and a one-line in-app status banner that states what is new in plain language. The changelog entry is pushed to your ReadMe documentation hub, and the banner copy is posted to a Slack channel where the product team can drop it into the in-app announcement bar.
When to use it
Use it when your docs changelog and in-app "what's new" banner habitually lag behind the actual release, leaving customers reading stale docs after an update. It fits teams that maintain hosted documentation in ReadMe and surface short release banners inside the product. Generating both from the same source release means the docs and the banner never disagree about what shipped.
How it works
- 1A GitHub trigger fires when a release is published, passing the version and notes.
- 2OpenAI formats the notes into a docs-ready changelog entry and a one-line banner string.
- 3The changelog entry is published to your ReadMe documentation hub.
- 4The banner copy is posted to a Slack channel for the team to load into the in-app bar.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect ReadMeAPI docs, changelog, auth.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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