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nba_player_dash_by_opponent

Read-only

Get Returns one player's by opponent splits as several result sets. Returns one player's by opponent splits as several result sets.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nba_player_dash_by_opponent"
  }
}

Input Schema

NameRequiredDescriptionDefault
seasonNoOptional season in YYYY-YY form, for example 2026-27. Defaults to the current NBA season.
per_modeNoOptional aggregation; defaults to PerGame.
league_idNoOptional league id; only 00 (NBA) is verified.
player_idNoRequired player id from nba-players or nba-team-roster, for example 1628398.
season_typeNoOptional season type; defaults to Regular Season.
measure_typeNoOptional statistic family; required by the upstream, defaults to Base.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The only behavioral detail the description adds is that results come back as 'several result sets', which is thin given an output schema exists; it says nothing about the upstream call's constraints or the fact that player_id is effectively required despite the empty required list.

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 text is short and front-loaded, but the single sentence is repeated twice with no added information, which is pure waste. Removing the duplicate would make it a clean one-liner.

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?

With a full input schema and an output schema, the description does not need to explain return values. Still, for a six-parameter analytics tool sitting among many similar split tools, the absence of any disambiguation or usage context leaves a real gap.

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?

Schema description coverage is 100%, so every parameter including season, per_mode, league_id, player_id, season_type, and measure_type is already documented in the schema. The description adds no format, default, or interaction detail beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource — one player's by-opponent splits — so the agent can tell it is player-scoped rather than team-scoped. However, the verb is a bare 'Get' and the sentence is duplicated verbatim, and nothing distinguishes it from siblings like nba_player_dash_by_clutch or nba_player_dash_by_game_splits beyond the phrase 'by opponent'.

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?

There is no when-to-use guidance, no mention of prerequisites, and no routing to alternatives such as the team-level counterpart or other split types. The agent must infer the use case entirely from the tool name.

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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