agent hive

CONTENT CREATION

Public Release Note to Multichannel Social Fanout

Takes an approved release note and stages tailored announcement variants for each social channel, posting the formatted versions out and confirming back in Slack.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook: release note approvedHTTP webhook
  • ActionFetch approved entry from NotionNotionNotion
  • ActionGenerate per-channel variants with LLMOpenAI
  • ActionPublish variants across channelsSocial publishing
  • OutputConfirm posted links in SlackSlack

What it does

Fans a single approved release note out into per-channel announcement copy and publishes it. It rewrites the same release into platform-appropriate variants — punchy for X/LinkedIn, longer for a community post — then sends them through the multichannel publisher and reports the result to Slack.

When to use it

When a release is approved and you want consistent-but-native announcements across every public channel without copy-pasting and reformatting by hand. Best paired with a workflow that produces the approved note upstream.

How it works

  1. 1A webhook trigger fires when a release note is marked approved, carrying the note body and version.
  2. 2The flow pulls the canonical changelog entry from Notion to ensure it's the final approved text.
  3. 3An LLM step generates tone- and length-tailored variants per target channel.
  4. 4The post-to-platforms step publishes each variant to its channel.
  5. 5A Slack confirmation reports which channels posted and links each live announcement.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect Social publishingCross-post to X, LinkedIn, Instagram, TikTok, and 4 more in one call.
  5. 5
    Connect SlackChannels, DMs, threads, mentions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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