CHATBOTS
Discord Ban Appeal Intake with Context Pull
Captures ban-appeal form submissions, pulls the appellant's original offense history from Postgres, has an LLM assess whether the appeal addresses the actual violations.
How it runs
The automated pipeline, trigger to output.
- TriggerAppeal form submitted via webhookHTTP webhook
- ActionRetrieve original offense history from PostgresPostgres
- ActionAssess appeal against offenses with OpenAIOpenAI
- LogicRoute spam appeals to archive, real ones forward
- OutputPost triaged appeal card to moderator channelDiscord
What it does
When a banned user submits an appeal via webhook form, this gathers the case file automatically: the original offenses from the offender ledger plus the appeal text. An LLM judges whether the appeal actually responds to what the user did wrong and assigns a triage tier (strong, weak, spam), then posts a single decision-ready card to the moderator channel.
When to use it
Use it when appeals arrive faster than mods can research each one. Instead of manually digging up why someone was banned, the bot assembles the full context and pre-sorts so reviewers spend time only on credible appeals.
How it works
- 1An HTTP webhook trigger receives the appeal form submission with the user's Discord ID and statement.
- 2A Postgres query retrieves that user's original offense history and ban reason.
- 3An OpenAI call compares the appeal against the offenses and assigns a triage tier with rationale.
- 4A logic step routes obvious spam appeals to an auto-archive path and real ones forward.
- 5The bot posts a triaged appeal card — history, statement, and tier — to the moderator channel for a ruling.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect DiscordCommunity channels + voice + bots.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
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Run this workflow in your colony.
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