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DanielTomaro13

sportsdata-mcp

euroleague_game

Read-onlyIdempotent

Fetch detailed information for one Euroleague game using its season and game code: scores, teams, referees, phase, and status.

Instructions

One game's detail by its per-season game code.

Returns: {id, gameCode, identifier, date, played, gameStatus, local:{club, score}, road:{club, score}, group, phaseType, referee1..4, audience} — a single object, NOT wrapped in {data}

Example: Game 1 of the season {"competition": "E", "season": "E2024", "gameCode": 1}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seasonYesSeason code. Required — part of the URL path.
gameCodeYesPer-season sequential game code (an integer like 1 or 330) — NOT the uuid. Required — part of the URL path.
competitionNoCompetition letter. One of: E, U.E
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds further useful context: 'Auth: none needed' and a clarification that the response is 'a single object, NOT wrapped in {data}'. These details go beyond the structured annotations, though it doesn't cover error behavior or rate limits.

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: a one-line purpose, a return shape summary, an example, and an auth note. Every sentence contributes useful information without redundancy.

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 read-only tool, the description covers the key aspects: what it returns (including the exact fields), an example call, and auth requirements. Given the annotations and schema already handle safety and parameter details, this is complete enough for an agent to invoke correctly.

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 has 100% description coverage, with each parameter clearly explained. The description's example demonstrates a valid call but adds little semantic value beyond what the schema already provides, so the baseline of 3 is appropriate.

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 states a specific verb and resource: 'One game's detail by its per-season game code.' It clearly distinguishes from sibling tools like euroleague_games (likely a list) and euroleague_game_stats (statistics) by focusing on a single game's full detail.

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 context for when to use the tool: to get one game's detail using its per-season game code. However, it does not explicitly mention alternative tools (e.g., euroleague_games for multiple games) or exclusions, so it falls short of the explicit alternative guidance seen in top-tier examples.

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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