SOCIAL MEDIA

Discord Reaction-Spike to Auto-Filed Linear Issue

When a Discord message crosses a negative-reaction threshold, classifies whether it describes a real product problem and, if so, opens a deduplicated Linear issue tagged…

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDiscord message crosses negative-reaction thresholdDiscordDiscord
  • ActionClassify complaint type and infer owning teamOpenAI
  • LogicDrop non-complaints; dedupe against existing Linear issuesLinearLinear
  • ActionCreate labeled Linear issue with source linkLinearLinear
  • OutputReturn new issue linkLinearLinear

What it does

This workflow turns a sudden pile-up of negative reactions on a Discord message into a tracked product issue. The moment a message accumulates enough thumbs-down, angry, or downvote reactions to clear your threshold, the workflow asks an LLM whether it actually describes a bug or product complaint (versus a joke or off-topic gripe). If it does, it files a Linear issue with the message text, link, and an inferred team label — skipping creation if a similar issue already exists.

When to use it

Use it when your community signals problems through reactions faster than they file tickets, and you want those signals to land in your engineering tracker automatically without spamming it with noise or duplicates.

How it works

  1. 1A Discord reaction event triggers when a message's negative-reaction count crosses the configured threshold.
  2. 2OpenAI classifies whether the message is a genuine product complaint and infers the responsible team.
  3. 3A logic step drops non-complaints and checks Linear for an existing similar issue.
  4. 4If it is a new, real complaint, a Linear issue is created with the source text, message link, and team label.
  5. 5The created issue link is delivered as the final output.

Set it up

What you configure once, before turning it on.

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

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