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sportiq-mcp

football_get_squad

Read-onlyIdempotent

Return a national team's World Cup squad.

Args: team: Team code or name (e.g. "ARG"). Without an API-Football key, the static seed serves an empty-but-valid squad (rosters are a follow-up).

Returns: data.squad: list of {name, number, position, age}. meta.source: adapter that served the data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYesTeam code or name (e.g. "ARG"). Without an API-Football key, the static seed serves an empty-but-valid squad (rosters are a follow-up).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
metaNo
errorNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses the static-seed fallback behavior, notes that rosters are a follow-up, and documents the meta.source adapter in the return. This adds useful context without contradicting the annotations.

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 compact and well-organized: a one-line summary, an Args section, and a Returns section. Every sentence earns its place, and the critical static-seed caveat is front-loaded alongside the parameter it affects.

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?

For a one-parameter read-only getter with an output schema and strong annotations, the description covers the return shape and the empty-squad edge case. Minor gaps like enumerating valid team codes are not necessary for correct invocation.

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 single team parameter is fully documented in the schema, and the description essentially repeats the same text: team code or name with the same static-seed caveat. Since schema coverage is 100%, the baseline of 3 applies; the description adds no new parameter meaning.

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 uses a specific verb-resource pair: "Return a national team's World Cup squad." This clearly distinguishes it from the many football tools for fixtures, odds, standings, and match stats, and from cricket_get_squad by sport and resource type.

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 provides clear context by warning that without an API-Football key, the static seed serves an empty-but-valid squad, which sets expectations for when the data is real versus a placeholder. However, it does not explicitly name alternatives or when-not-to-use conditions, so it stops short of full routing guidance.

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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