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DanielTomaro13

sportsdata-mcp

dabble_sports

Read-onlyIdempotent

Retrieve all supported sports with IDs and names to map competition sportIds back to their sport details. Includes racing and hidden flags.

Instructions

The 24 sports Dabble offers (Rugby League, Australian Rules, Football, Basketball, Cricket, Tennis, Horse Racing, …), each with id + name. Join sportId from a competition back to its sport here.

Returns: {status, data:[{id, name, isRacing, isHidden}]}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnly, openWorld, and idempotent hints. The description adds useful context beyond that: it states that auth is not needed, and it discloses the exact return shape ({status, data:[{id, name, isRacing, isHidden}]}) and the fixed count of 24 sports. This gives the agent a solid understanding of what to expect.

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 highly concise and well-structured: it leads with the core purpose, then the return shape, then auth. Every sentence earns its place. No fluff or repetition of schema data.

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 lookup tool with no parameters, the description is fully complete. It explains the returned fields, the function (join with competitions), and authentication requirements. There is no output schema, so the explicit return format is critical and provided. The context from sibling tools further clarifies its niche.

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?

The tool takes no parameters (empty input schema), so parameter explanations are unnecessary. The baseline for a zero-parameter tool is 4, and the description appropriately provides no redundant parameter details.

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 lists the 24 sports offered by Dabble, each with an ID and name. It also explains its role as a lookup for joining sportId from competitions, distinguishing it from sibling tools like dabble_competitions or dabble_active_competitions.

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?

The description provides clear usage context: use this to join sportId from a competition back to its sport. It doesn't explicitly mention when not to use it, but the purpose is specific enough that the agent can infer when it's appropriate. No exclusions or alternatives are listed, so it's clear but not exhaustive.

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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