infersports

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

Name	Required	Description	Default
`limit`	No
`sport`	No
`league`	No
`status`	No
`timezone`	No

TDQS

A4.8/5.0

Behavior5/5

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

The annotations already set readOnlyHint=true. The description adds significant behavioral details: each fixture carries status, live score, clock, and summary; clock is null pre-match; timezone affects summary display. It clarifies that clock gives the real minute rather than estimation.

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 concise: a one-line purpose, a paragraph on response fields, then a clear parameter list. It front-loads the core purpose and uses minimal but sufficient detail.

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 tool has 5 parameters, no required params, 0% schema coverage, and no output schema, the description covers all necessary aspects: purpose, output structure (clock, summary), parameter semantics, and defaults. It is complete enough for an agent to use the tool correctly.

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 description coverage is 0%, but the description fully compensates by explaining each parameter: sport values ('football'/'basketball'), status ('live'/'scheduled'/'finished'), league (fuzzy-matched or external id), limit (1-200, default 50), and timezone (IANA format). This adds 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?

The description clearly states the tool lists today's fixtures in UTC, with the example usage 'what games are on today / right now?'. It specifies the verb 'list' and resource 'fixtures', distinguishing it from siblings like 'list_events' which may cover a different scope.

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 provides clear context for when to use the tool (current day's matches) and explains all filter parameters (sport, status, league, limit, timezone) with defaults. However, it does not explicitly state when not to use it or compare with sibling tools.

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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TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: compare_lines contrasts bookmakers, compare_prob evaluates external probabilities, find_arbitrage detects arbitrage opportunities, find_match resolves fixtures, etc. Even related tools like get_sharp_line (one-call line) and compare_lines (event_id-based comparison) are complementary rather than overlapping. No ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., compare_lines, find_match, list_bookmakers). Verbs like compare, find, get, list, scan, score are uniform. No mixing of conventions or vague names.

Tool Count5/5

With 17 tools covering fixture discovery, odds retrieval, comparisons, value/arb detection, line movement, results, and slate scanning, the count is well-scoped for a sports betting odds API. No unnecessary tools, and the set feels complete without being bloated.

Completeness5/5

The tool surface covers the full lifecycle: find matches (find_match, list_events, list_today_matches), get odds (get_match_odds, get_sharp_line, compare_lines), detect value/arb (find_value, find_arbitrage, scan_slate), analyze lines (get_opening_line, explain_handicap, score_prob), and retrieve results (get_result, list_results). No obvious gaps for the stated read-only odds analysis domain.

Resources

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