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by net.crawlora
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nba_lineups

Read-only

Get NBA lineup dashboard. Returns the lineup dashboard for one lineup size and measure: one row per lineup with GROUP_ID, GROUP_NAME, TEAM_ID, TEAM_ABBREVIATION and the counting/rate columns for the requested measure. The payload is large — the five-man sample was about 712 KB — so request it once and page locally. GroupQuantity is pinned to the one verified size, 5.

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_lineups"
  }
}

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.
season_typeNoOptional season type; defaults to Regular Season.
measure_typeNoOptional statistic family; Base, Advanced, Misc, Scoring, Defense or Opponent. Defaults to Base.
group_quantityNoOptional lineup size; only 5 is verified and is the default.

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

A3.6/5.0
Behavior4/5

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

The annotations already establish read-only and open-world behavior. The description adds useful behavioral context beyond that: the payload is large (~712 KB in the sample), it should be requested once and paged locally, and only size 5 is verified.

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 front-loaded, uses three tight sentences, and every sentence contributes: purpose/return shape, payload warning, and the fixed lineup-size constraint.

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?

An output schema exists, so return-value explanation is not strictly required, but the description still clarifies row granularity and fields. It covers payload behavior and the verified-size constraint; the main gap is the absence of when-to-use guidance versus sibling tools.

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 the baseline is 3. The description reinforces that the tool operates on one lineup size and one measure and that GroupQuantity is pinned to 5, but this largely repeats what the schema already documents rather than adding new parameter semantics.

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 uses a specific verb and resource: "Get NBA lineup dashboard," then clarifies the row grain (one row per lineup) and key fields. It is clear what the tool returns, though it does not explicitly distinguish itself from nearby lineup or box-score siblings.

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?

It gives operational guidance about the large payload and paging locally, plus the pinned GroupQuantity constraint. However, it does not say when to choose this tool over alternatives such as nba_lineup_shot_chart or box-score tools, nor does it state exclusions.

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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