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DanielTomaro13

sportsdata-mcp

supercoach_settings

Get competition state including current round, next round, lockout timings, and user/league counts for a sport and season. Use this to find the correct round for player projections.

Instructions

Competition state for one game+season: competition.current_round (last round scored), next_round (the one to project), is_lockout / lockout_start / lockout_end, is_closed, num_users, num_leagues. Call this FIRST to learn which round to pass to supercoach_players. Tiny (~15 KB).

Returns: {system, game, content, competition:{current_round, next_round, status, is_lockout, is_partial_lockout, lockout_start, lockout_end, is_closed, num_users, num_leagues}}

Example: AFL current round / next round

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
minNo
modeNoclassic
yearYes
sportYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the output structure in detail, mentions it is tiny (~15 KB), and implies read-only behavior (competition state). However, it does not explicitly state read-only, authentication needs, or rate limits, so it's slightly above average but not fully transparent.

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 well-structured and front-loaded with key functionality. It includes a return structure example and usage hint. While it could be slightly more concise, every sentence adds value, and the example aids understanding.

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 no output schema and no annotations, the description needs to be comprehensive. It provides return structure and usage guidance but fails to document parameters (0% coverage). This incompleteness means some critical decisions for invocation are left to inference, making it adequate but not fully complete.

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 schema has 0% description coverage for its 4 parameters. The description does not explain any parameter (sport, year, min, mode). For example, 'min' and 'mode' are not mentioned at all. This is a major gap, leaving the agent to guess parameter meaning from names alone.

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 that the tool returns competition state for a game+season, listing specific fields like current_round, next_round, lockout info, etc. It distinguishes itself from sibling tool supercoach_players by indicating it should be called first to learn which round to pass.

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

Usage Guidelines5/5

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

The description explicitly instructs 'Call this FIRST to learn which round to pass to supercoach_players.' This provides clear guidance on when and how to use the tool relative to its sibling, including a direct alternative mention.

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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