CHATBOTS

Discord Support Thread Auto-Resolver with 'Solved' Reaction Archiving

Watches a Discord support channel, drafts a proposed fix in-thread, then archives the thread once a member adds the 'solved' reaction and logs the resolution to Postgres.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew message opens a support threadDiscordDiscord
  • ActionDraft a proposed fix from the questionOpenAI
  • ActionPost the proposed fix into the threadDiscordDiscord
  • LogicWait for and match the 'solved' reaction
  • ActionArchive the resolved threadDiscordDiscord
  • OutputLog the resolution to PostgresPostgreSQLPostgres

What it does

Turns a busy Discord support channel into a self-closing queue. When someone opens a support thread, the workflow reads the question, drafts a concrete suggested fix, and posts it as the first reply. It then waits for a human to confirm by adding the configured 'solved' reaction emoji. On confirmation, it archives the thread and writes a structured resolution record to Postgres for reporting.

When to use it

Use it when your team runs front-line support inside Discord and threads pile up unresolved. It is ideal for OSS communities or product Discords where moderators want an AI first-pass answer plus a clean, auditable close on every solved thread.

How it works

  1. 1A new message in the support channel triggers the run.
  2. 2An OpenAI step reads the thread question and drafts a proposed fix.
  3. 3The draft is posted back into the Discord thread as a reply.
  4. 4The flow watches the thread for the 'solved' reaction emoji.
  5. 5A logic step checks whether the reaction matches the configured solved emoji.
  6. 6On match, Discord archives the thread.
  7. 7The resolution (question, proposed fix, resolver, timestamp) is inserted into Postgres.

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 PostgresAny Postgres URL — query, write, migrate.
  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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