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nba_team_stats

Retrieve NBA league-wide team statistics for a season, with Base or Advanced measures and PerGame or Totals aggregation, returning one row per team and source column headers.

Instructions

NBA league-wide team statistics table. Returns the league-wide team statistics table for one season, measure and aggregation: one row per team with the columns the source publishes for that measure, keyed by the source's own column names such as TEAM_ID, TEAM_NAME, GP, W, L, W_PCT, PTS and PLUS_MINUS. Base and Advanced are the two verified measures, and PerGame and Totals the two verified aggregations; the columns differ between measures, so read the response's headers list rather than assuming a fixed set.

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_team_stats"
  }
}

Input Schema

Name	Required	Description
`season`	No	Season in YYYY-YY form; defaults to the current NBA season
`per_mode`	No	Aggregation; PerGame or Totals
`league_id`	No	League id; only 00 (NBA) is verified
`season_type`	No	Season type; Regular Season or Playoffs
`measure_type`	No	Statistic family; Base or Advanced

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.17.20Nov 12, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses return shape: one row per team, source column names, variable columns by measure, and advises reading headers. It omits permissions, pagination, rate limits, and error behavior, so it is not complete.

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?

Front-loads purpose, then details return shape and parameter caveats. Slightly dense but every sentence earns its place; the initial fragment is redundant with title-like phrasing.

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 tool with five optional params and no output schema, the description explains row granularity and return-column variability and tells the agent to read headers. It is largely complete, though it could mention the default season and that all params are optional.

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?

Schema description coverage is 100%, establishing a baseline of 3, but the description adds that only Base/Advanced and PerGame/Totals are verified, and that columns vary by measure. This meaningfully supplements the enums, which list additional unverified values.

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?

States a specific verb ('Returns') and resource ('league-wide team statistics table') for one season, measure and aggregation. It clearly identifies the data domain but does not explicitly contrast with sibling team tools like nba_team_game_logs or nba_team_details.

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

Usage Guidelines3/5

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

Provides implied usage through 'one season, measure and aggregation' and flags verified measures/aggregations, but gives no explicit when/when-not guidance or alternatives. An agent must infer that this is for league-wide team stats rather than player or game-log stats.

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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