SUMMARIZATION
Daily Discord support harvest into Notion answer-candidate queue
Once a day, reads the prior 24 hours of a Discord support channel, finds threads that reached a resolution.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires after peak support hours
- ActionFetch last 24h of channel messages and group into threadsDiscord
- LogicKeep only threads with a resolution signal
- ActionDistill each thread into a Q/A candidateOpenAI
- OutputCreate review rows in Notion answer-candidate databaseNotion
What it does
Every morning it scans a Discord support channel for the last day of conversation, isolates the threads where a user's problem actually got solved, and turns each one into a tidy question-and-answer candidate in Notion. A support lead opens Notion, skims the queue, and promotes the good ones to the real macro library.
When to use it
When your community answers the same questions repeatedly in Discord and that knowledge evaporates in the scrollback. Run it daily so the macro library grows from real, already-validated solutions instead of guesswork.
How it works
- 1A daily schedule fires after the channel's busiest hours.
- 2The flow pulls the previous 24 hours of messages and groups them into threads.
- 3A logic step keeps only threads showing a resolution signal (an accepted reply, a thanks, or a reaction).
- 4OpenAI distills each kept thread into a one-line question and a concise, reusable answer, stripping names and noise.
- 5Each candidate is created as a row in a Notion review database with status "Needs review" and a link back to the source thread.
Set it up
What you configure once, before turning it on.
- 1Connect DiscordCommunity channels + voice + bots.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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