AI AGENTS

Discord repeat-offender pattern review and escalation

On a daily schedule, an agent aggregates a member's recent flags across channels, decides whether a pattern warrants a ban recommendation.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily scheduled pattern review
  • ActionAggregate recent flags by member from DiscordDiscordDiscord
  • ActionClassify each flagged message with Hugging FaceHugging FaceHugging Face
  • LogicFilter to members over the repeat threshold
  • ActionAgent builds timeline + drafts escalation
  • OutputOpen per-member review thread in DiscordDiscordDiscord

What it does

Looks past single messages to spot patterns. Each day the agent groups recent flagged messages by member, evaluates whether someone has crossed from one-off slips into a sustained pattern, and — only when the history justifies it — drafts a ban or extended-mute recommendation with the supporting timeline.

When to use it

Use it when individual reports keep getting dismissed in isolation but the same handful of members are quietly accumulating warnings. It surfaces the repeat-offender story that no single moderator sees, while keeping the final ban decision firmly with a human.

How it works

  1. 1A daily scheduled trigger starts the run.
  2. 2The agent reads the last N days of flagged messages from Discord, grouped by member.
  3. 3A Hugging Face classifier tags each message so the agent can weigh severity over time.
  4. 4Logic filters to members exceeding a repeat-flag threshold.
  5. 5The agent builds a per-member timeline and drafts an escalation recommendation with rationale.
  6. 6It opens a Discord review thread per flagged member for moderator approve/override.

Set it up

What you configure once, before turning it on.

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

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