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OrygnsCode

Omnicord - Discord server management MCP for AI agents

Bulk ban

bulk_ban
Destructive

Ban up to 200 users at once for raid cleanup. Preview first, then confirm with a token to execute. Reports successes and failures.

Instructions

Ban up to 200 users at once by ID, for raid cleanup. Safe to call directly: the first call changes nothing and returns a preview plus a confirm_token; repeating the call with the token performs the bans. Reports which bans succeeded and which failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
guildNoGuild (server) name or ID. Omit to use the default guild.
reasonNo
dry_runNo
user_idsYesUser IDs to ban.
confirm_tokenNo
delete_message_secondsNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals a critical two-phase behavior (preview with confirm_token, then execution) that is not visible in the schema or annotations. It also discloses that it reports per-ban success/failure, going well beyond the destructiveHint annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, no redundancy, front-loaded with the core purpose. The safety preview behavior is explained in a compact, highly readable way.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core behavior, limits, and output. It could additionally mention edge cases like invalid IDs or rate limits, but for the tool's complexity, the provided information is sufficient to call it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is low (33%), so the description must compensate. It clarifies the confirm_token flow and the 200-user limit, but it does not explain optional parameters like reason or delete_message_seconds, leaving some semantics to inference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Ban'), resource ('users'), scope ('up to 200, by ID'), and context ('raid cleanup'). This clearly distinguishes it from sibling tools like ban_member and prune_members.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool ('raid cleanup') and explains the safe two-step invocation pattern. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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