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Sports Games & Scores

sports.bdl.games
Read-onlyIdempotent

Get NBA and NFL game results by date — scores, teams, status (Final/In Progress/Scheduled). Filter by date, season, or team. Covers all NBA and NFL games with real-time scores (BallDontLie)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoGame date (YYYY-MM-DD, e.g. "2026-03-29"). Returns all games on that date
limitNoMax results (1-25, default 10)
sportNoSport league: "nba" (default) or "nfl"nba
seasonNoSeason year (e.g. 2025 for 2025-26 season)
team_idNoFilter by team ID (get IDs from bdl.teams)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world. The description adds behavioral details: returns scores, teams, status (Final/In Progress/Scheduled), and real-time scores. This adds value beyond annotations without contradiction.

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?

Two sentences with no wasted words. First sentence states purpose and output fields, second lists filters and data source. Front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a robust input schema (100% coverage), informative annotations, and presence of an output schema, the description completes the picture by clarifying the sports covered, output fields, and data source. No gaps for an agent to select and invoke the tool correctly.

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 baseline is 3. The description mentions filtering by date, season, or team, which maps to parameters, but does not add meaning beyond what the schema already provides for each parameter (e.g., sport enum, limit, date format).

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 clearly states the verb 'Get' and specifies the resource: 'NBA and NFL game results by date — scores, teams, status'. It distinguishes from siblings by explicitly limiting coverage to NBA and NFL, unlike other sports tools that may cover different leagues or sports.

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?

The description mentions filtering options ('Filter by date, season, or team') and states the tool covers all NBA and NFL games, providing clear context. However, it does not explicitly exclude other sports or name alternatives like sports.basketball.games or sports.football.*.

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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