CHATBOTS

Discord Ban-Recommendation Agent with Human Review Gate

An agent reviews a flagged offender's complete record against your moderation policy, drafts a ban recommendation with reasoning.

CategoryChatbots
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerUser added to ban-review list in DiscordDiscordDiscord
  • ActionPull offender history from PostgresPostgreSQLPostgres
  • ActionLoad moderation policy from NotionNotionNotion
  • ActionAgent reasons over evidence and drafts verdictOpenAI
  • LogicFormat structured verdict into review card
  • OutputPost recommendation to review queue with approve/rejectDiscordDiscord

What it does

For an offender flagged as ban-worthy, an agent reads their entire ledger, weighs it against your written moderation policy, and produces a structured recommendation: ban, temp-mute, or warn, with the evidence and policy clauses cited. It posts the recommendation to a review queue channel where a moderator approves or rejects — the bot never bans autonomously.

When to use it

Use it when bans carry real cost (paid members, regulated communities) and every removal must be defensible. The agent does the tedious evidence-gathering; the human keeps the final call.

How it works

  1. 1A Discord trigger fires when a user is added to the ban-review list (a command or reaction).
  2. 2The agent pulls the offender's full history from Postgres and the current policy text from Notion.
  3. 3The agent reasons over both and produces a structured verdict with cited evidence and a confidence level.
  4. 4A logic step formats the verdict into a review card.
  5. 5The bot posts the card to the review-queue channel with approve and reject controls, holding for a human decision.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DiscordCommunity channels + voice + bots.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect NotionPages, databases, comments.
  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.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.