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rishijatia

Fantasy Premier League MCP Server

by rishijatia

analyze_fixtures

Assess upcoming fixtures for players, teams, or positions to identify favorable and challenging matchups, with options to include blank and double gameweek info.

Instructions

Analyze upcoming fixtures for players, teams, or positions

    Args:
        entity_type: Type of entity to analyze ("player", "team", or "position")
        entity_name: Name of the specific entity
        num_gameweeks: Number of gameweeks to look ahead
        include_blanks: Whether to include blank gameweek info
        include_doubles: Whether to include double gameweek info

    Returns:
        Fixture analysis with difficulty ratings and summary
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_nameNo
entity_typeNoplayer
num_gameweeksNo
include_blanksNo
include_doublesNo
Behavior2/5

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

With no annotations, the description carries the full burden. It only mentions the return includes difficulty ratings and summary, but does not disclose side effects, prerequisites, authentication needs, or limitations. For an analysis tool, this is a significant gap in behavioral transparency.

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 well-structured with a clear first sentence, followed by a readable Args block and Returns line. Every sentence earns its place, conveying necessary information without unnecessary verbosity.

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?

The tool has 5 parameters and no output schema, so the description should explain the return format more thoroughly. It gives a vague 'fixture analysis with difficulty ratings and summary' but does not describe edge cases like null entity_name, invalid entity_type, or how the output is structured. It is adequate but missing important context.

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

Parameters5/5

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

The schema has no parameter descriptions (0% coverage), but the description's Args section explains every parameter in detail, including allowed values for entity_type and the meaning of include_blanks and include_doubles. This fully compensates for the schema 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 the tool analyzes upcoming fixtures for players, teams, or positions, which is a specific verb+resource+scope. It distinguishes itself from sibling tools like analyze_player_fixtures by explicitly covering three entity types, making the broader scope evident.

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

Usage Guidelines3/5

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

The description implies usage for fixture analysis but provides no explicit guidance on when to use this tool versus alternatives. It does not mention that analyze_player_fixtures is a more specialized sibling or when to prefer one over the other, leaving the choice to the agent.

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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