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DanielTomaro13

sportsdata-mcp

nba_playbyplay

Retrieve a detailed play-by-play log for a single NBA game, including every action with clock, score, and description. Requires gameId.

Instructions

Event-level play-by-play log for one game from the CDN: every action with clock, score, player and description. gameId from nba_scoreboard_today / nba_schedule.

Returns: {game:{gameId, actions:[{actionNumber, period, clock, scoreHome, scoreAway, description}]}}

Example: Play-by-play for one game.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gameIdYes
Behavior3/5

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

No annotations are provided, so the description must bear the full burden of behavioral disclosure. It describes the return format and fields but does not mention whether the operation is read-only, any rate limits, or potential side effects. This is adequate but leaves gaps.

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 relatively concise and front-loaded with the main purpose. It includes a useful example of the return structure. It could be slightly shorter, but the example adds clarity without being overly verbose.

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?

The description covers the input (gameId source), output structure (actions with fields), and an example. Given the simplicity of the tool (one parameter, no output schema), it provides sufficient context. It does not mention pagination or limits, but these are likely not needed for a single-game log.

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

Parameters4/5

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

The description adds meaning to the gameId parameter by specifying where to find it (nba_scoreboard_today / nba_schedule). Since schema description coverage is 0%, this compensates well, providing essential context 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 it provides event-level play-by-play log for one game, including clock, score, player, and description. It references the source (CDN) and gives an example of the return format. While it does not explicitly differentiate from siblings like nba_boxscore or nba_schedule, the purpose is unambiguous.

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

Usage Guidelines4/5

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

The description instructs the user to obtain gameId from nba_scoreboard_today or nba_schedule, providing clear context on how to find the required parameter. It does not specify when to use this tool over alternatives, but the context is sufficient for a single-parameter tool.

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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