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

Annotations already establish that this is a read-only, idempotent, non-destructive, non-open-world tool. The description adds useful scope by listing the NBA and NFL split types and noting that it is a "Pro" capability, but it does not clarify access requirements, data freshness, response shape, or limits. With annotations covering the safety profile, this is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler, opening directly with the core action. The semicolon-separated NBA/NFL branch is dense but efficient. It is slightly packed and run-on, but every phrase contributes to scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only, annotated tool with four fully documented parameters and no output schema, the description gives a useful inventory of the returned split categories for both leagues. It omits return formatting and some access details, but those gaps are minor for an agent deciding whether and how to invoke it.

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

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

Schema description coverage is 100%, so the schema already documents league, season, player_id, and teammate_id. The description reinforces the teammate concept with "with/without a teammate," but it adds no syntax, defaults, or additional meaning beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states a specific verb and resource: it returns player splits, including NBA on/off, clutch, garbage-time, and teammate splits, or NFL usage shares. The metric list makes the tool's data scope concrete. It does not, however, explicitly distinguish itself from sibling tools such as player_profile or props_research.

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

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

The description names the data types available but gives no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or sibling tools, so the agent must infer selection criteria from the tool name and metric list.

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