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Gameball MCP Server

Gameball MCP Server

by Ahmedelmonady
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Docs: Get Tutorial

docs-get-tutorial

Get the full step-by-step tutorial for a specific Gameball topic, such as referrals or points redemption. Ideal when you need detailed implementation instructions.

Instructions

Get a specific Gameball tutorial by topic. Use when you need the full step-by-step tutorial content. For broad questions, use docs-lookup-topic instead.

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": {
      "topic": "<topic>"
    },
    "name": "docs-get-tutorial"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicYesTutorial topic, e.g. "referral", "points-redemption", "order-handling"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It states the tool retrieves a specific tutorial and returns 'full step-by-step tutorial content,' which implies a read-only operation. However, it does not explicitly mention authentication requirements, potential side effects, or limitations beyond the sibling differentiation, leaving some behavioral details unspecified.

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?

The description is concise and front-loaded with the core purpose. It uses three short sentences to convey what the tool does, when to use it, and how it differs from a sibling, with no redundant filler.

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

Completeness5/5

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

For a simple tool with one parameter and no output schema, the description is complete. It states the exact use case, the alternative for broader queries, and hints at the return content ('full step-by-step tutorial content'). No critical information is missing given the tool's low complexity.

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?

The input schema covers the single parameter 'topic' with a description and examples, achieving 100% schema_description_coverage. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 applies.

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's function: 'Get a specific Gameball tutorial by topic.' It uses a specific verb ('get') and resource ('tutorial'), and distinguishes from sibling tools by explicitly mentioning docs-lookup-topic as an alternative for broad questions.

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?

The description gives explicit when-to-use guidance: 'Use when you need the full step-by-step tutorial content.' It also provides an exclusion: 'For broad questions, use docs-lookup-topic instead,' which clearly directs agents away from this tool for broader queries.

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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