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WNBA minutes and rotations

invoke_wnba_rotations
Read-onlyIdempotent

Average minutes and plus minus per player across the most recent WNBA games, with the last game date. Use it to spot a role change before pricing catches up.

Input Schema

NameRequiredDescriptionDefault
teamNoTeam abbreviation, for example LVA, NYL, IND or MIN. ESPN codes such as LV or NY work too.
limitNoMaximum rows to return. The plan limit applies on top.
playerNoPlayer name, for example A'ja Wilson.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description usefully adds the aggregation window semantics (averages over most recent games, exposure of last game date), but leaves ambiguity about how many games constitute 'recent' and says nothing about the plan limit mentioned in the schema.

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?

Two tight sentences, metrics front-loaded ahead of the use-case hint, with zero filler. Every clause carries information.

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 correctly takes on the burden of describing the return payload – per-player minutes, plus-minus, and last game date. Parameters are fully covered by the schema. Only the 'most recent games' window size and plan-limit interaction remain underspecified.

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 team, limit and player are all documented at the schema level with examples and the plan-limit caveat. The description adds no parameter-level detail beyond that, so the baseline of 3 is appropriate.

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?

States a specific resource (WNBA minutes/rotations) and the exact metrics returned – average minutes and plus-minus per player over recent games, plus last game date. It does not, however, differentiate itself from close siblings like invoke_wnba_player_pool or invoke_nba_rotations, which an agent would have to disambiguate by schema inspection.

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?

'Use it to spot a role change before pricing catches up' gives a clear analytical intent, but offers no when-not guidance and never names an alternative tool (e.g. projections or player_pool) or the condition that selects this one over them. Usage is implied rather than prescribed.

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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