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DanielTomaro13

sportsdata-mcp

cricketdata_scorecard

Read-onlyIdempotent

Fetch a cricket match's full scorecard by match ID, with batting and bowling figures for each innings.

Instructions

Full scorecard: batting and bowling figures per innings.

Returns: {status, data:{id, name, scorecard:[{inning, batting:[{batsman:{id, name}, r, b, '4s', '6s', sr, 'dismissal-text'}], bowling:[{bowler:{id, name}, o, m, r, w, eco}], extras, totals}]}} — SHAPE FROM VENDOR DOCS. Cricket abbreviations: r runs, b balls, sr strike rate, o overs, m maidens, w wickets, eco economy.

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 match's scorecard {"id": ""}

Auth: needs your own key in CRICKETDATA_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesMatch id.
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior. The description adds context beyond these by stating that an API key is required ('needs your own key in CRICKETDATA_API_KEY') and warning that the response shape is from vendor documentation and has not been verified, advising the agent to inspect the actual payload.

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 purpose first, then return shape, abbreviations, warning, example, and auth. While relatively long, the information is relevant and organized, with the key purpose stated at the beginning.

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 provides a detailed JSON return shape, explains cricket abbreviations, gives an example, and notes the unverified nature of the shape. This gives the agent sufficient context to handle the response, despite the lack of a formal output schema.

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 describes the single parameter 'id' as 'Match id.' The description provides an example call using {'id': '<match id>'}, but this adds little beyond the schema. Since schema coverage is 100%, the baseline of 3 is appropriate.

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 states 'Full scorecard: batting and bowling figures per innings,' clearly identifying the tool's function. This distinguishes it from sibling tools like cricketdata_match_info and cricketdata_current_matches.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It includes an example but does not explain when to use it over other scorecard or match tools, leaving the agent to infer usage from the name and purpose.

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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