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DanielTomaro13

sportsdata-mcp

mlb_game_context_metrics

Read-onlyIdempotent

Fetch MLB game context metrics like leverage index and win probabilities for a specified game and optional time snapshot.

Instructions

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

Returns: {game, leverageIndex, homeWinProbability, awayWinProbability}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gamePkYesGame id. Required — part of the URL path.
timecodeNoPoint-in-time snapshot.
Behavior4/5

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

The description adds valuable behavioral context beyond the annotations: it states the exact return object shape and explicitly notes that no authentication is needed. It also clarifies the temporal scope ('current/most-recent state'), which helps set expectations. With readOnlyHint and idempotentHint already present, this extra context is sufficient.

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 compact and well-structured: purpose in the first sentence, return shape in the second, and auth in the third. Every sentence contributes value without redundancy or filler, and the key information is front-loaded.

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

Completeness4/5

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

For a read-only tool with full schema coverage and clear annotations, the description covers the return contract, temporal scope, and auth requirement. The main gap is the lack of guidance on how this tool relates to overlapping siblings, but the core context is sufficiently complete for basic usage.

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?

The input schema already fully documents both parameters (gamePk required, timecode optional) with descriptions, so the baseline applies. The description's mention of 'current/most-recent state' hints at timecode semantics but does not add meaningful extra detail beyond the schema.

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?

The description clearly states that the tool provides context metrics for a game, listing specific metric types (leverage, win-probability, run-expectancy) and scope ('current/most-recent state'). While it is clear, it does not explicitly differentiate from the sibling tool mlb_game_win_probability, which likely overlaps.

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?

The description gives no guidance on when to use this tool versus alternatives like mlb_game_win_probability or mlb_live_feed. It neither specifies use cases nor exclusions, leaving the agent to infer the appropriate context from the name and return fields.

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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