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Get roster

get_roster
Read-onlyIdempotent

Full roster grouped by position, with jersey numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already disclose read-only, idempotent, non-destructive behavior. The description adds useful output-organization details (grouped by position, jersey numbers) but no further behavioral traits such as data source or response size.

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?

A single, front-loaded sentence that states the output shape and its key attribute (jersey numbers) with no 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?

For a simple read-only tool with one obvious required parameter and annotations covering safety, the description plus schema are sufficient to invoke it. It describes the return grouping and fields; only the lack of parameter format guidance prevents a higher score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for the required 'team' parameter, and the description does not explain accepted formats, whether it is a team name or ID, or how to obtain valid values. The parameter is self-evident in context, but the description does not compensate for the missing schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns a full roster grouped by position with jersey numbers, and the name/title supply the get/resource framing. It does not explicitly contrast with sibling tools, but the roster resource is distinct from injury reports, odds, player stats, schedule, and team lists.

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?

No when-to-use guidance or alternatives are provided; the only signal is the name get_roster. An agent must infer that this is for roster queries and is not told how to choose among the 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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct resource: injuries, odds, player stats, roster, schedule, and the universe of teams. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tools use a clear verb_noun pattern: get_* for specific resources and list_teams for the full collection. This is consistent and predictable.

Tool Count5/5

Six tools is well-scoped for a read-only sports data server covering NFL and NBA information. Each tool covers a meaningful slice of the domain without bloat.

Completeness4/5

The surface covers the main pre-game and season data needs: teams, rosters, schedule, stats, injuries, and odds. Only a minor gap exists for something like game results or standings, which is not central to the apparent betting/team-info focus.

Resources