CUSTOMER SUPPORT
Cluster repeated unanswered Discord questions into a KB draft
Scans the support Discord for questions that went unanswered, groups the recurring ones into clusters.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionFetch recent Discord support messagesDiscord
- LogicKeep questions with no team reply
- ActionCluster unanswered questions by topicOpenAI
- LogicDrop clusters below frequency threshold
- ActionDraft KB article per clusterOpenAI
- OutputCreate review-tagged Notion draftNotion
What it does
It finds the questions your community keeps asking that nobody answered, and turns the most common ones into a ready-to-review KB article instead of letting them disappear in the channel scroll.
When to use it
Run it on a schedule (daily or weekly) when your support Discord has more inbound questions than your team can answer in threads, and you want documentation to catch up to what people actually ask.
How it works
- 1A daily schedule kicks off the run.
- 2It pulls recent messages from the support Discord channel and isolates ones shaped like questions with no reply or reaction from a team member.
- 3An LLM step embeds and clusters the unanswered questions, scoring each cluster by how many distinct users hit it.
- 4A filter keeps only clusters above a frequency threshold so one-off questions are ignored.
- 5For each surviving cluster, an LLM drafts a KB article: title, problem statement, step-by-step answer, and source message links.
- 6The draft lands in a Notion review database tagged "needs-review" so a human approves before it goes live.
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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