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cricket_get_squad

Read-onlyIdempotent

Retrieve the squad roster for any cricket team. Optionally specify a series ID to get the tournament-specific lineup, including player names, roles, and credits.

Instructions

Return the squad roster for a cricket team, optionally for a specific series.

Args: team: Team code or name (e.g. "MI", "CSK", "IND", "AUS"). series_id: Optional. Series ID to pull the tournament-specific squad. If omitted, falls back to static seed data.

Returns: data.players: list of players with name, role, and credits. meta.source: adapter that served the data (cricapi / static_seed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYesTeam code or name (e.g. "MI", "CSK", "IND", "AUS").
series_idNoOptional. Series ID to pull the tournament-specific squad. If omitted, falls back to static seed data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
metaNo
errorNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare this as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations by disclosing the fallback to static seed data and the meta.source adapter behavior, which helps the agent understand possible data provenance.

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 and well-structured with a clear one-line purpose, Args section, and Returns section. Every sentence provides useful information, and the most important statement is front-loaded. There is no redundant or filler content.

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?

For a simple two-parameter, read-only tool with full schema coverage, an output schema, and rich annotations, the description is fully sufficient. It explains the optional behavior, fallback source, and return fields, leaving no important operational gap for an agent to call it correctly.

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?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description repeats the examples and fallback explanation without adding significant new meaning beyond the schema. This matches the baseline of 3 for fully covered parameters.

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 opens with a clear, specific verb and resource: 'Return the squad roster for a cricket team'. It clearly differentiates this tool from the many other cricket and football tools by naming the exact data domain. The optional series scoping is also stated immediately.

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 supply series_id and what happens when it is omitted, falling back to static seed data. It does not explicitly name alternatives or exclusions, but the purpose and optional parameter behavior are clear enough for an agent to decide when to invoke it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.