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Football/Soccer Fixtures & Scores

sports.football.fixtures
Read-onlyIdempotent

Get football fixtures, live scores, and results filtered by date, league, or team. Covers 2000+ leagues in 171 countries.

Instructions

Football/soccer fixtures, live scores, and results — filter by date, league (Premier League, La Liga, Champions League...), team. 2000+ leagues, 171 countries. 362+ fixtures per day (API-Sports)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate in YYYY-MM-DD format (e.g. "2026-03-20"). Returns all fixtures for that day.
leagueNoLeague ID (e.g. 39 = Premier League, 140 = La Liga, 78 = Bundesliga)
seasonNoSeason year (e.g. 2025)
teamNoTeam ID to filter fixtures
liveNoSet to true to get only live/in-play fixtures

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, establishing safe read-only behavior. The description adds scale (2000+ leagues, 171 countries) and mentions live scores, but does not provide additional behavioral traits beyond what annotations already cover.

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?

The description is extremely concise with no wasted words. It front-loads the core purpose and immediately follows with filtering options and scale, making it efficient for quick understanding.

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?

Given the presence of an output schema, the description does not need to detail return values. It sufficiently explains the tool's purpose, filtering capabilities, and scale. The annotations confirm safety, completing the context for a read-only query tool.

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% with all parameters described. The description reiterates filtering by date, league, and team but adds no new semantic meaning beyond the schema descriptions.

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 provides football/soccer fixtures, live scores, and results with filtering by date, league, and team. It distinguishes from sibling tools like sports.football.leagues and sports.football.standings by specifying the focus on match events and scores.

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 implies usage for obtaining fixtures and scores with filtering, but does not explicitly state when to use alternatives. However, the sibling tool names (leagues, standings) make the differentiation clear based on context.

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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