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DanielTomaro13

sportsdata-mcp

laliga_match

Read-onlyIdempotent

Get a single La Liga match by its slug; played matches include scores and formations.

Instructions

One match by SLUG (from laliga_matches; the long temporada-… slug, not the numeric id which 404s). For a played match adds scores + formations.

Returns: {match:{id, slug, name, home_team, away_team, home_score, away_score, home_formation, away_formation, competition, gameweek, date, status, attempt, ball}}

Auth: works without a key; LALIGA_SUBSCRIPTION_KEY unlocks more if set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesMatch slug (from laliga_matches.matches[].slug). Required — part of the URL path.
Behavior4/5

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

Annotations already declare read-only and idempotent, so the description adds conditional data behavior (scores/formations only for played matches) and auth context (works without key, subscription key unlocks more). This adds meaningful value beyond 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-structured: purpose, returns, and auth in separate sections. Every sentence contributes, with no fluff or 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 one-parameter tool with no output schema, the description covers purpose, slug source, result fields, conditional behavior, and auth. The explicit Returns list effectively substitutes for an output schema.

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 schema covers the slug parameter with origin guidance, but the description adds critical nuance about the slug format (long temporada slug vs. numeric id) and a 404 pitfall, going beyond what the schema provides.

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 retrieves one match by SLUG, referencing laliga_matches as the source and distinguishing from plural list tools. It also specifies what data is returned (scores + formations for played matches).

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 explicit guidance on where the slug comes from (laliga_matches) and warns against using the numeric id which 404s. However, it does not directly compare with alternative match-detail tools or state when not to use it, though that is implied by 'One match'.

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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