SUMMARIZATION

Agent-driven publish of approved Discord answers into Confluence

When a harvested answer candidate is approved in Notion, an agent expands it into a polished, on-brand Confluence FAQ page, links related existing docs.

CategorySummarization
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNotion candidate marked ApprovedNotionNotion
  • ActionRead approved Q/A and linked Discord sourceDiscordDiscord
  • ActionSearch related Confluence pages and draft articleConfluenceConfluence
  • ActionPublish the FAQ page to the docs spaceConfluenceConfluence
  • OutputReply in Discord thread with link; mark Notion PublishedDiscordDiscord

What it does

This is the publish stage of the harvest pipeline. Once a human approves a candidate in Notion, an agent rewrites the rough Q/A into a complete, on-brand Confluence article, cross-links it to related existing pages, and closes the loop by dropping the live doc link back into the Discord thread that started it.

When to use it

When approved knowledge should become real, searchable documentation rather than sitting in a queue. The agent handles the judgment-heavy work of phrasing, structure, and finding related docs to link.

How it works

  1. 1The trigger fires when a Notion candidate's status flips to "Approved".
  2. 2The agent reads the approved Q/A and the linked source Discord thread for context.
  3. 3It searches existing Confluence pages for related material to reference.
  4. 4It drafts a structured FAQ page, then publishes it to the documentation space.
  5. 5It posts the published link back to the original Discord thread and marks the Notion row as "Published".

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect DiscordCommunity channels + voice + bots.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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