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nba_player_career_stats

Retrieve an NBA player's season-by-season and career regular-season and postseason statistics by player ID, including games, minutes, and points totals.

Instructions

NBA player season-by-season and career statistics. Returns one player's career statistics as several tables: the season-by-season regular-season line, the career regular-season totals, the season-by-season postseason line and the career postseason totals. Verified columns are SEASON_ID, TEAM_ID, GP, GS, MIN and PTS. per_mode PerGame or Totals is validated against the values verified on this endpoint.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "player_id": "<player_id>"
    },
    "name": "nba_player_career_stats"
  }
}

Input Schema

Name	Required	Description
`per_mode`	No	Aggregation; PerGame or Totals
`league_id`	No	League id; only 00 (NBA) is verified
`player_id`	Yes	Player id from nba-players or nba-team-roster

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.17.20Nov 12, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the return shape (four separate result tables) and the verified column set (SEASON_ID, TEAM_ID, GP, GS, MIN, PTS). It says nothing about error behavior, empty seasons, or whether postseason data may be absent, and the remark about per_mode validation is vague about what happens with unverified values.

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?

Three sentences, front-loaded with what the tool returns, followed by the concrete output structure and the verified column list. No filler or repetition.

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?

No output schema exists, so the description does the necessary work of describing the four returned tables and the verified columns. Combined with fully covered parameters, it is nearly complete, with only missing sibling/usage routing and edge-case behavior as gaps.

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 coverage is 100%, so the three parameters are already documented, giving a baseline of 3. The description adds some meaning by explaining that per_mode is an aggregation choice and that columns are verified, but it muddies things by mentioning 'PerGame or Totals' while the schema enum permits only PerGame.

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 names a specific resource and scope: one player's season-by-season and career statistics, broken into four named tables. It is clear enough to distinguish from generic stat tools, though it never explicitly differentiates itself from siblings such as nba_player_stats or nba_player_game_logs.

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 statement of when to choose this tool over the many sibling stat tools, nor any prerequisites or exclusions. The only usage-adjacent content is a note that per_mode values are validated against the endpoint, which is a constraint rather than guidance on selection.

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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