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OrygnsCode

Omnicord - Discord server management MCP for AI agents

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Resolve Discord names by fragment to find channels, roles, and members with their IDs. Get ranked candidates when unsure of exact names.

Instructions

Universal name resolver. Give it a name fragment and get ranked candidates across channels, roles, and members with their IDs. Use this when unsure what an entity is called or to grab an ID once and reuse it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
guildNoGuild (server) name or ID. Omit to use the default guild.
queryYesName or fragment to look up.
typesNoRestrict the search. Default: all three.
Behavior4/5

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

With readOnlyHint annotation already establishing safety, the description adds useful behavioral context: results are 'ranked candidates' and include IDs, and the search spans multiple entity types. It doesn't mention pagination or rate limits, but the annotation lowers the bar and the added context is meaningful.

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?

Two tight sentences: the first states the core function, the second gives the use case. Everything earns its place; no fluff or redundancy.

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 tool is relatively simple with a clear input schema and read-only annotation. The description explains the output (ranked candidates with IDs) and the optional guild semantics are covered in the schema. It's complete enough for effective selection and invocation, though pagination or result limits are not mentioned.

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 description coverage is 100%, so the baseline is 3. The description reinforces the meaning of query as a 'name fragment' and types as channels/roles/members, but doesn't add significant new details beyond the schema. It's adequate but not additive.

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 clearly and specifically states what the tool does: a 'Universal name resolver' that takes a name fragment and returns ranked candidates across channels, roles, and members with IDs. This distinct verb and resource make it easy to differentiate from siblings like search_members or list_channels.

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 explicitly says 'Use this when unsure what an entity is called or to grab an ID once and reuse it,' giving a clear trigger for when to invoke the tool. It doesn't explicitly state when not to use it or name alternatives, but the guidance is strong and immediately actionable.

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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