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universal-mcp

Fpl Universal MCP Server

fpl_analyze_fixtures

Analyze upcoming Fantasy Premier League fixtures for players, teams, or positions, with configurable gameweek range and blank/double gameweek insights.

Instructions

Analyze upcoming fixtures for players, teams, or positions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_nameNoName of the specific entity
entity_typeNoType of entity to analyze ("player", "team", or "position")player
num_gameweeksNoNumber of gameweeks to look ahead
include_blanksNoWhether to include blank gameweek info
include_doublesNoWhether to include double gameweek info

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full burden of explaining behavior, but it only says 'Analyze upcoming fixtures' without defining what analysis is performed, what is returned, or how blanks/doubles affect results. The parameter names hint at some behavior, but the description itself adds little beyond the tool name.

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 focused sentence with no filler, and the core action and scope are front-loaded. It is appropriately short for a simple tool, though it could earn a 5 if it also included a brief usage clue.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and five parameters including a nullable entity_name, a one-sentence description is insufficient. The agent cannot tell whether entity_name is needed for all entity types, what the output looks like, or how this differs from overlapping sibling tools.

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?

Schema description coverage is 100%, so parameters like entity_type, num_gameweeks, include_blanks, and include_doubles are already self-explanatory. The description adds no further detail, particularly for the nullable entity_name, which remains vague ('Name of the specific entity') with no example or relationship to entity_type.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear action ('Analyze upcoming fixtures') and the resource scope ('players, teams, or positions'), making its general purpose understandable. It does not explicitly distinguish itself from the similarly named sibling fpl_analyze_player_fixtures, though the entity_type parameter hints at a broader scope.

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 about when to use this tool instead of fpl_analyze_player_fixtures, fpl_analyze_players, or the blank/double gameweek tools. An agent must infer the use case from the name and schema alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.