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by net.crawlora
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faceit_ban_reasons

Read-only

Get FACEIT ban reason enum. Returns the closed ban-reason enum the ban-list filter accepts. The upstream names these values in its own validation error, so they are server-validated. Pass one as the reason parameter of faceit-banlist to filter the ban list.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "faceit_ban_reasons"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely non-obvious context: the set is closed, and the values are server-validated because upstream surfaces them in its own validation error, so an agent knows it cannot guess values. It stops short of describing pagination/error behavior, but an output schema is present to cover the return shape.

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

Conciseness4/5

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

Four short sentences, front-loaded with purpose, then scope, then validation provenance, then routing. The opening two sentences overlap slightly ("ban reason enum" / "closed ban-reason enum"), a small redundancy but no filler.

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?

An output schema exists so return values need no explanation, and the description covers purpose, provenance, and downstream use for a zero-argument enum tool. The only friction is naming the consumer as "faceit-banlist" while the sibling is listed as faceit_banlist, which could momentarily confuse an agent matching tools.

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

Parameters4/5

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

Zero parameters, so there is no parameter meaning to add and the baseline is 4. The one relevant semantic detail, that the returned values are the accepted argument for another tool's reason parameter, is supplied.

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?

States a specific verb and resource ("Get FACEIT ban reason enum") and immediately constrains scope: it returns the closed enum the ban-list filter accepts. That distinguishes it cleanly from faceit_banlist, which consumes the values rather than producing them.

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

Usage Guidelines5/5

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

Explicit chaining guidance: "Pass one as the reason parameter of faceit-banlist to filter the ban list." It says both what this tool is for and where its output goes next, leaving nothing to inference.

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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