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DanielTomaro13

sportsdata-mcp

cricketdata_player_info

Read-onlyIdempotent

Retrieve a cricket player's full profile and career batting/bowling statistics across Test, ODI, and T20I formats by providing a player ID.

Instructions

One player's profile and career batting/bowling statistics.

Returns: {status, data:{id, name, dateOfBirth, role, battingStyle, bowlingStyle, placeOfBirth, country, playerImg, stats:[{fn:'batting'|'bowling', matchtype:'test'|'odi'|'t20i', stat:'m'|'runs'|'avg', value}]}} — SHAPE FROM VENDOR DOCS. NOTE stats is LONG format: one row per (function, format, statistic), not a nested object.

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: One player's career {"id": ""}

Auth: needs your own key in CRICKETDATA_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesPlayer id (from cricketdata_players).
Behavior4/5

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

The description goes beyond the readOnlyHint/openWorldHint annotations by explicitly warning that the return shape is from vendor docs and unverified, advising the agent to inspect actual payloads. It also discloses the long-format `stats` structure and the need for a CRICKETDATA_API_KEY, adding valuable behavioral context without contradiction.

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 structured with clear sections: purpose, return shape, caveat, example, and auth. While it is somewhat lengthy, every section carries necessary information—especially the unverified shape warning—and there is minimal redundancy.

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?

With no output schema, the description compensates by fully documenting the return shape, the long-format nuance, and the authentication requirement. It is reasonably complete for a single-parameter tool, though it does not cover error conditions or missing-data behavior.

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 input schema already provides 100% coverage for the single `id` parameter, including provenance ('from cricketdata_players'). The description's example merely repeats the schema structure and adds no semantic depth beyond what is already documented.

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 'One player's profile and career batting/bowling statistics,' which identifies the specific resource (player) and scope (single player). This distinguishes it from sibling tools like cricketdata_players (likely a list) and cricketdata_scorecard, making the purpose unambiguous.

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 usage when you have a player ID and need profile/career stats, and the example shows the input. However, it does not explicitly state when to prefer this tool over alternatives, nor does it provide exclusions or alternative tool references.

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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