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infersports

by dev.infersports
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List Today's Matches

list_today_matches
Read-only

List today's (UTC) fixtures — "what games are on today / right now?".

Each fixture carries its status, live score, the live match ``clock`` (upstream minute text,
verbatim e.g. "1h 25" / "2h 47" / "ht") when in-running, and a ready-to-read ``summary`` (live
score & clock, or the kickoff time). Read ``clock`` for the real minute rather than estimating it
from kickoff. ``clock`` is null pre-match.

Args:
    sport: optional filter — "football" or "basketball".
    status: optional filter — "live", "scheduled" or "finished".
    league: optional league filter — a name (fuzzy-matched, e.g. "World Cup") or an external id ("lg_…").
    limit: max fixtures to return (1–200, default 50).
    timezone: optional IANA timezone (e.g. "America/New_York", "Asia/Shanghai") to render each
        fixture's kickoff in its ``summary`` as local time; default UTC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sportNo
leagueNo
statusNo
timezoneNo

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 provide readOnlyHint: true, so the read-only nature is covered. The description adds valuable context: it explains that clock is the live minute verbatim and that clock is null pre-match, and that summary is ready-to-read. This goes beyond annotations and helps the agent interpret the output correctly.

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 well-structured: a one-sentence purpose, a paragraph on what each fixture carries, and a clear Args section. Every sentence earns its place; there is no fluff. The key behavior (today's matches) is front-loaded.

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?

Given there is no output schema, the description explains the output fields (status, live score, clock, summary) and how timezone affects the summary. It covers all parameters. It doesn't mention pagination or ordering, but for a filterable list tool this is adequate. A minor gap, hence 4.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the full burden for parameters. It explicitly explains each one: sport, status, league (fuzzy match or external id), limit (with range and default), and timezone (with examples). This adds significant meaning beyond the bare schema.

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?

States a specific verb and resource: 'List today's (UTC) fixtures' — clearly scoped to today's matches. It distinguishes from siblings like list_results (results) and list_events (broader events) by the 'today' scope, so an agent knows exactly what it does.

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

Usage Guidelines3/5

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

The description implies when to use it (when you need today's fixtures) and offers filters, but it does not explicitly name alternatives like list_events or list_results or state when not to use it. Usage context is clear but no exclusions are given, so it falls at 'implied usage'.

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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