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nba_game_detail

Fetch an NBA game's summary from its ten-digit ID: status, clock, duration, attendance, venue, officials, series, and per-period team scoring. Use for game-level context, not player stats.

Instructions

NBA game summary detail from nba.com. Returns one game's summary detail from nba.com's game page, read from the page's embedded JSON state: status and clock, game duration, attendance and sellout flag, venue id, name, city, state, country and timezone, the officiating crew with names and jersey numbers, series text, and each team's per-period scoring with a derived game total. Use nba-box-score for per-player statistics; this route is the game-level summary the box score does not carry.

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": {
      "game_id": "<game_id>"
    },
    "name": "nba_game_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
game_idYesTen-digit game id from nba-scoreboard

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.20

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the data source ('read from the page's embedded JSON state'), which signals a read-only, scrape-derived route with the fragility that implies. It enumerates what is returned, but says nothing about behavior for invalid game ids, live vs. final games, or error responses.

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 the source and scope, followed by the routing advice. The return-field enumeration is long but earns its place because no output schema exists; only minor pruning would be possible.

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 must explain return values and it does so thoroughly, down to per-period scoring and derived game totals. The remaining gap is operational behavior (errors, live-game state) rather than content coverage.

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% and the single game_id parameter already documents its ten-digit format and provenance (nba-scoreboard). The description adds no additional meaning about the parameter, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Returns one game's summary detail from nba.com's game page') and explicitly delineates itself from nba-box-score. An agent can tell exactly which entity and granularity this tool serves without opening the schema.

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

Usage Guidelines4/5

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

It routes the agent explicitly: use nba-box-score for per-player statistics, and states this route is the game-level summary the box score does not carry. That gives a clear selection rule against the most likely alternative, though it offers no guidance on preconditions (e.g. whether the game must be final or live) or on invalid inputs.

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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