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by net.crawlora
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nba_team_stats_leaders

Read-only

Get one NBA statistical leaderboard and return the ranked player rows for the requested category. stat_category is required and accepts PTS, REB or AST; scope is S for the player leaderboard, with optional season in YYYY-YY form, season_type and per_mode. The upstream rejects a missing stat_category with HTTP 403, so the service validates it locally first; other leader categories are not verified and must not be guessed.

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_leaders"
  }
}

Input Schema

NameRequiredDescriptionDefault
scopeNoOptional player-pool scope; S (all players) is verified. Defaults to S.
seasonNoOptional season in YYYY-YY form, for example 2026-27. Defaults to the current NBA season.
per_modeNoOptional aggregation; PerGame or Totals. Defaults to PerGame.
league_idNoOptional league id; only 00 (NBA) is verified.
season_typeNoOptional season type; Regular Season or Playoffs. Defaults to Regular Season.
stat_categoryNoRequired ranked statistic; PTS, REB or AST. This parameter is required by the upstream.

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

A3.8/5.0
Behavior4/5

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

Beyond readOnlyHint/openWorldHint, the description discloses real behavioral detail: the upstream returns HTTP 403 on a missing stat_category, so the service validates locally first, and unverified values must not be guessed. It also implicitly conveys that scope= S and league_id=00 are the verified paths. It does not describe row-count limits or how the leaderboard is ranked/truncated, which is the main remaining gap.

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?

Two sentences, front-loaded with what the tool returns, then the parameter and failure-mode facts. Dense but every clause carries information; the only slight drag is that the 403 explanation is packed into the same sentence as the valid category list.

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?

With an output schema and annotations present, the description covers the essentials an agent needs: required category, accepted values, defaults for season/season_type/per_mode, and the verification boundary on unverified values. Guidance on choosing among sibling leaderboard tools is the one omission for a 6-parameter tool in a crowded NBA namespace.

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 coverage is 100%, so a 3 would be the baseline, but the description adds value the schema does not: it flags stat_category as effectively required even though the schema's required array is empty, and it marks scope=S and league_id=00 as the verified values. This meaningfully compensates for the schema's misleading 'required: 0' signal.

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 gives a specific verb and resource: 'Get one NBA statistical leaderboard and return the ranked player rows for the requested category.' It also clarifies a subtle mismatch with the tool's name (team_stats_leaders) by stating the rows are player rows on the S leaderboard. It stops short of naming a sibling leaderboard tool (e.g. nba_homepage_leaders) to contrast against, so it is clear but not sibling-differentiated.

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?

Guidance is present but framed as constraints rather than when-to-use: stat_category 'is required and accepts PTS, REB or AST' and 'other leader categories are not verified and must not be guessed.' That usefully narrows the call, but the description never says when to pick this tool over the many other NBA leaderboard/stats siblings, nor what to do instead when a non-PTS/REB/AST category is needed.

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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