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DanielTomaro13

sportsdata-mcp

cricketdata_current_matches

Read-onlyIdempotent

Get details of cricket matches currently in progress or starting soon, with live scores, teams, and venue information.

Instructions

Matches in progress or starting soon, with live scores.

Returns: {status:'success', data:[{id, name, matchType:'t20'|'odi'|'test', status, venue, date, dateTimeGMT, teams:[str], teamInfo:[{name, shortname, img}], score:[{r, w, o, inning}], series_id, matchStarted, matchEnded}], info:{hitsToday, hitsLimit}} — SHAPE FROM VENDOR DOCS. Score fields are terse: r runs, w wickets, o overs.

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: Live and upcoming matches

Auth: needs your own key in CRICKETDATA_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetNoPage offset (25 per page).
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses the return shape, explicitly warns that the shape is unverified and from vendor docs, instructs the agent to inspect actual payloads, and states the auth requirement (CRICKETDATA_API_KEY). This is valuable behavioral context that annotations alone do not 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 front-loaded with purpose, then provides the return shape, a critical caveat, an example, and auth info. It is somewhat long due to the embedded JSON shape, but each element earns its place. The 'Example: Live and upcoming matches' line is slightly redundant with the first sentence, preventing a perfect score.

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 no output schema, the description fully covers the return payload shape, notes field abbreviations (r/w/o), warns about reliability, and mentions auth. It is complete and self-sufficient for an agent to invoke the tool and handle its response appropriately.

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 only parameter (offset) is fully described in the schema at 100% coverage ('Page offset (25 per page)'), so the description does not need to add much. It adds no new semantic detail about the parameter itself, matching the baseline for high schema coverage.

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 what the tool does: returns matches in progress or starting soon with live scores. The name and first line together distinguish this from sibling cricketdata_matches, which likely covers all matches. The scope is specific and actionable.

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 first sentence gives a clear temporal context for when to use this tool ('in progress or starting soon'), and the example 'Live and upcoming matches' reinforces this. However, no explicit alternatives or when-not-to-use guidance is provided, though the context is clear enough.

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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