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nba_team_dash_pt_shots

Read-only

Get Returns one team's tracking shot dashboard: the shot breakdowns the upstream computes for that team (by touch time and shot type), as several result sets. Returns one team's tracking shot dashboard: the shot breakdowns the upstream computes for that team (by touch time and shot type), 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_pt_shots"
  }
}

Input Schema

NameRequiredDescriptionDefault
seasonNoOptional season in YYYY-YY form; defaults to the current NBA season.
team_idNoRequired team id from nba-standings.
per_modeNoOptional aggregation; defaults to PerGame.
league_idNoOptional league id; only 00 (NBA) is verified.
season_typeNoOptional season type.

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

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the bar is lower, and the description does add one useful fact: results come back 'as several result sets'. It says nothing about what 'dash' implies (rolling/averaged splits), data freshness, or row volumes beyond that.

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 same sentence, including the odd leading 'Get', is repeated verbatim twice. That is pure waste and signals an unpolished definition, though the first sentence is reasonably front-loaded.

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?

With annotations, an output schema, and full schema coverage, the description covers the essentials, but for a dashboard tool with many near-identical siblings it should clarify the touch-time/shot-type breakdown versus the plain shot tools. The duplicated text also edges out content that could have been useful.

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 schema already documents season, team_id, per_mode, league_id, and season_type. The description adds nothing about any parameter; baseline 3 applies when the schema does the work.

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 states a specific verb and resource ('Returns one team's tracking shot dashboard') and names the content ('shot breakdowns by touch time and shot type'). 'One team's' implicitly separates it from the player-level siblings like nba_player_dash_pt_shots, but no sibling is named explicitly, so it falls short of a 5.

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 or when-not-to-use guidance at all. The description never distinguishes this from nba_team_pt_shot, nba_opp_pt_shot, or nba_player_dash_pt_shots, leaving the agent to guess from the 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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