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DanielTomaro13

sportsdata-mcp

laliga_standing

Retrieve the complete La Liga standings for a given season, including each team's matches, points, goal difference, and position.

Instructions

Full league table for a season — 20 entries with played/won/drawn/lost/goals_for/goals_against/goal_difference/points/position + full team object (shield, colours).

Returns: {total, standings:[{position, previous_position, played, won, drawn, lost, goals_for, goals_against, goal_difference, points, team:{id, slug, name, shortname, opta_id, shield}}]}

Example: 2025/26 LALIGA EA SPORTS table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
Behavior3/5

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

With no annotations, the description carries the full burden. It implies a read-only fetch by describing the returned data, but does not explicitly state that it is safe, idempotent, or what authentication is required. It adds some behavioral context through the return structure example.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph with a clear first sentence, followed by a return structure and example. It is concise but could be more front-loaded with the parameter explanation.

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

Completeness3/5

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

Given the tool is simple (one parameter, one output), the description provides the return structure and an example, which is helpful. However, it lacks parameter guidance and usage context, leaving gaps for an agent to correctly invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The sole parameter 'slug' has no description in the input schema (0% coverage) and the tool description does not explain its meaning or acceptable values. The example '2025/26 LALIGA EA SPORTS' provides a hint but no semantic clarity. This is a significant gap.

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 it returns a 'Full league table for a season' with 20 entries and specific fields. It distinguishes itself from sibling laliga tools (e.g., laliga_match, laliga_player) by focusing on the standings table.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or when not to use it. The description is purely declarative.

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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