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sebazai

faceit-mcp

by sebazai

faceit_getQueuesByEntityFilters

List queues for a FACEIT game by filtering with entity type and ID to find specific queues.

Instructions

Retrieve queues by filters on FACEIT

Use to list queues for a game with arbitrary entity filters. If you already know the region use getQueuesByRegion; if you know the queue_id use getQueueById.

Endpoint: GET /games/{game_id}/queues

Parameters:

  • game_id (path, str, required): The id of the game

  • entity_type (query, str, required): The type of the entity

  • entity_id (query, str, required): The id of the entity

  • offset (query, int | None (min 0)): The starting item position

  • limit (query, int | None (min 1, max 20)): The number of items to return

Returns: Queues list

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
game_idYes
entity_typeYes
entity_idYes
offsetNo
limitNo
Behavior4/5

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

No annotations are provided, so the description carries full burden. It correctly implies a read-only operation (GET endpoint) and lists parameters. However, it does not disclose authentication needs or rate limits, which prevents a perfect score.

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?

The description is concise, starting with purpose, then usage guidelines, endpoint, and parameter list. It is well-structured and easy to scan, though slightly lengthy for some preferences.

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

Completeness2/5

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

Given the absence of an output schema, the description should detail the return structure beyond 'Queues list'. This is insufficient for an agent to understand what data to expect, leaving a significant completeness gap.

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 0%, so description must add meaning. It provides type and required status for all parameters, and adds min/max constraints for offset and limit. However, for required parameters entity_type and entity_id, it merely restates the name without explaining acceptable values or formats.

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 states the tool retrieves queues by filters on FACEIT and lists queues for a game with arbitrary entity filters. It distinguishes itself from siblings by mentioning alternative tools: getQueuesByRegion and getQueueById.

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 guidance is given: use this tool for arbitrary entity filters; if you know the region, use getQueuesByRegion; if you know the queue_id, use getQueueById. This directly addresses when to use alternatives.

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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