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DanielTomaro13

sportsdata-mcp

apisports_basketball_games

Read-onlyIdempotent

Fetch basketball games by date, league, team, or season. Get scores, teams, and status for leagues like NBA, EuroLeague, NBL, and more.

Instructions

Basketball games worldwide (NBA, EuroLeague, NBL and many more) by date or league.

Returns: {response:[{id, date, status:{long, short}, league:{id, name, season}, teams:{home, away}, scores:{home:{quarter_1, quarter_2, quarter_3, quarter_4, over_time, total}, away:{…}}}]} — SHAPE FROM VENDOR DOCS. Note season is a '2023-2024' STRING here; the football host uses an integer year.

NOTE: this shape is from the vendor's documentation and has NOT been verified against a live response (we hold no key for this provider). Treat it as approximate — inspect the actual payload before relying on a field name.

Example: A day's games {"date": "2024-01-15"}

Auth: needs your own key in API_SPORTS_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoYYYY-MM-DD.
teamNoTeam id.
leagueNoLeague id.
seasonNoSeason as a SPAN for this sport, e.g. '2023-2024' — not a single year like football.
timezoneNoIANA zone.
Behavior5/5

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

Annotations already declare read-only, idempotent, and open-world hints, but the description adds substantial behavioral context: the detailed return shape, the caveat that the shape is unverified and approximate, the season field being a string rather than integer, and the API key requirement. This exceeds what annotations alone provide.

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?

The description is moderately long due to the return shape and caveats, but it is logically structured: purpose, return shape, verification warning, example, auth. Every sentence serves a purpose, though the return shape block could be considered verbose. It is concise for the information conveyed.

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?

For a read-only games listing tool, the description is quite complete: it explains purpose, parameters, return structure, auth, and even disclaims the unverified shape, compensating for the lack of an output schema. Minor gaps exist, such as behavior when no parameters are supplied, but overall it is well-rounded.

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?

The schema covers all five parameters with meaningful descriptions, so the baseline is 3. The description adds an example and reinforces the date/league query modes, but it does not materially extend beyond the schema's parameter definitions. No parameter explanation is missing.

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 tool returns basketball games worldwide from multiple leagues ('NBA, EuroLeague, NBL and many more') and highlights the two primary query dimensions ('by date or league'). This differentiates it from sibling tools like apisports_basketball_standings and other sports' games tools, even though a verb like 'list' is implicit.

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 gives concrete context for when to use the tool: to fetch basketball games by date or league, with an example date payload. It does not explicitly name alternatives or exclusion criteria (e.g., when not to use it vs. basketball standings), but the scope is unambiguous enough for selection.

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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