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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

faceit_rules

Fetch one page of published FACEIT competition rules with limit/offset paging, including rule IDs, names, games, organizer IDs, timestamps, and full markdown rule bodies.

Instructions

FACEIT published competition rules. Returns one page of the published FACEIT competition rule sets: rule id, name, game, organizer id, creation and update timestamps and the full rule body in markdown. The upstream accepts entity filters but ignores them, so this route exposes only paging. Paging uses limit and offset.

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_rules"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoOptional page size, 1-100; default 20.
offsetNoOptional non-negative row offset.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.20

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose key traits: one page per call, paging via limit/offset, the silent ignoring of filter parameters, and the full markdown rule body in the response. It does not cover auth requirements, rate limits, or whether total counts are returned for pagination.

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?

Four short sentences, front-loaded with what the tool returns, then the important upstream quirk, then the paging mechanics. No filler or restatement of the tool name.

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?

No output schema exists, and the description compensates by listing the returned fields. For a simple two-parameter read tool this is nearly complete; the only shortfall is that paging termination (whether a total count is available) is not addressed.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds that paging is the only supported parameterization and that filter-style parameters will not work despite appearing accepted upstream. That is meaningfully more than the schema conveys on its own.

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 first sentence names a specific verb and resource ('Returns one page of the published FACEIT competition rule sets'), and the second enumerates the returned fields (rule id, name, game, organizer id, timestamps, markdown body). No sibling in the provided list serves the same FACEIT rules resource, so an agent can identify this tool unambiguously.

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 explicitly tells the agent that entity filters are accepted upstream but ignored, so only paging is exposed — that is real when-not guidance preventing a wasted filtering attempt. It stops short of naming alternative tools or stating when this tool should be preferred over any other, but the usage context is clear.

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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