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DanielTomaro13

sportsdata-mcp

mlb_game_context_metrics

Get leverage index, win probability, and run expectancy context metrics for an MLB game state.

Instructions

Context metrics for a game — leverage, win-probability and run-expectancy context for the current/most-recent state.

Returns: {game, leverageIndex, homeWinProbability, awayWinProbability}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gamePkYes
timecodeNo
Behavior3/5

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

With no annotations, the description must disclose behavioral traits. It states the tool returns certain metrics for the 'current/most-recent state', implying a read-only operation with no side effects. However, it does not clarify data freshness, any restrictions, or what happens if the game is not found. This is adequate 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.

Conciseness5/5

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

The description is two sentences covering purpose and return format with no extraneous words. It is front-loaded and efficiently communicates essential information.

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?

Despite the tool's moderate complexity (2 parameters, no output schema), the description lacks parameter explanations. It does provide the return structure, but the omission of parameter semantics leaves significant gaps for correct invocation.

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 two parameters (gamePk integer required, timecode string optional) with 0% coverage from description. The description never mentions these parameters, their purpose, constraints, or how to use them. The agent gets no added value beyond the schema itself, which is insufficient.

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 returns context metrics (leverage, win-probability, run-expectancy) for a game's current/most-recent state. The verb 'returns' and listing of specific fields leaves no ambiguity about what the tool does, and it distinguishes itself from siblings like mlb_game_win_probability which likely returns only win probability.

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 such as mlb_game_win_probability or mlb_boxscore. The description does not mention use cases, prerequisites, or exclusions, leaving the agent to infer appropriateness from the tool name alone.

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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