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nba_team_dash_by_clutch

Read-only

Get Returns one team's by clutch splits as several result sets. Returns one team's by clutch 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_team_dash_by_clutch"
  }
}

Input Schema

NameRequiredDescriptionDefault
seasonNoOptional season in YYYY-YY form, for example 2026-27. Defaults to the current NBA season.
team_idNoRequired team id from nba-standings, for example 1610612738.
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; 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
Behavior3/5

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 description adds one genuinely useful behavioral trait — that the response comes back as several result sets — but says nothing about the upstream requirement hinted in the schema, rate limits, or which splits are included.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The single sentence is duplicated word-for-word, which is pure waste and a visible defect in the definition. There is also no front-loaded structure beyond the resource noun phrase.

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?

The rich input schema and the presence of an output schema mean return values and parameters need not be explained here. However, for an open-world six-parameter tool in a dense sibling cluster, the description does nothing to explain what 'clutch splits' contain or why an agent would pick this over the player or game-splits variants.

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% with six well-documented optional parameters (season, team_id, per_mode, league_id, season_type, measure_type), so the schema carries parameter meaning. The description adds nothing beyond it, making the baseline 3 appropriate.

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 text conveys a specific resource (one team's clutch splits) but the phrasing is garbled — 'Get Returns one team's by clutch splits as several result sets' — and the sentence is repeated verbatim. It never distinguishes this from the sibling nba_player_dash_by_clutch or the other team split tools.

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 prerequisites, and no mention of alternatives despite ~30 sibling tools covering player clutch splits, game splits, last-N-games, and opponent splits. The agent must infer selection from the tool name alone.

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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