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by net.crawlora
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faceit_hubs

Read-only

Get FACEIT hubs by id. Returns summary rows for up to 20 hub ids supplied as a repeated ids parameter: hub id, game and region, name, organizer, avatar, player count, category, publication state, relationship type, child ids and organizer tier. An unknown id is simply omitted from the item list. Hub ids come from faceit-hub-memberships.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ids": "<ids>"
    },
    "name": "faceit_hubs"
  }
}

Input Schema

NameRequiredDescriptionDefault
idsYesRequired hub UUIDs; repeat the parameter for up to 20 hubs.

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

A3.9/5.0
Behavior4/5

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

Annotations only cover read-only and open-world; the description adds genuinely new behavior: batch cap of 20 ids and the fact that an unknown id is silently omitted rather than erroring. That omission rule is the kind of detail an agent needs and would otherwise have to discover by failure.

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?

Two sentences, front-loaded with the action, followed by the return contents and an edge case. The long enumerated field list ('hub id, game and region, name, organizer, avatar, player count…') partly duplicates the output schema and is the least efficient part.

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?

With an output schema present, the description needn't explain return values, and it covers scope, id source, batch limit, and unknown-id handling. What's left unstated is failure behavior when more than 20 ids are supplied and any ordering guarantee for the returned items.

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 100% and the schema already states 'repeat the parameter for up to 20 hubs,' so the description's repeated-ids and 20-limit language largely restates it. The only real addition is the omission semantics for unknown ids, which is behavioral rather than parameter-level.

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

Purpose4/5

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

The description opens with a specific verb and resource ('Get FACEIT hubs by id') and adds that it returns summary rows, which implicitly separates it from the detailed variant. It stops short of naming faceit_hubs_detailed or faceit_hub explicitly, so the differentiation is inferable rather than stated.

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?

It gives a clear entry point by saying hub ids come from faceit-hub-memberships and defines the batch size limit. It does not state when to prefer faceit_hub or faceit_hubs_detailed instead, so the alternative-selection guidance is only partial.

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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