sportsdataio_mlb_games_by_date

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

Even though annotations declare readOnlyHint, openWorldHint, and idempotentHint, the description adds valuable behavioral context: the output shape is from vendor docs and NOT verified against a live response, so agents should treat fields as approximate. It also discloses the auth requirement (key in one of several SPORTSDATAIO_* env vars), which goes beyond the annotations and is critical for successful invocation.

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 well-structured and efficiently conveys essential information: the core purpose, the return shape, a caveat about accuracy, an example, and auth notes. Every sentence earns its place, with no fluff or repetition. The format is scannable and front-loaded with the most important details.

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 single-parameter tool with no output schema, the description is remarkably complete. It provides the full list of expected fields, warns about the unverified shape, gives a working example, and specifies auth requirements. The caveat about inspecting the actual payload further prepares the agent for potential schema drift, making the description sufficient for confident use.

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?

The input schema already provides 100% coverage for the single `date` parameter, including format and required status. The description adds an example but no additional semantic meaning beyond what the schema states. Baseline 3 is appropriate since the schema does the heavy lifting and the description does not introduce new parameter nuances.

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 what the tool does: 'MLB games on a date, with probable pitchers and the line.' It explicitly includes the return fields and distinguishes itself from the keyless official `mlb` provider, making the purpose and scope unambiguous. The sibling tools for other sports are implicitly differentiated by naming MLB and date.

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 provides explicit usage guidance by noting that the keyless official `mlb` provider is 'deeper for everything except the line and the DFS layer,' implying this tool is the choice when line/DFS data is needed. It also gives a concrete example of the required date parameter, which helps the agent understand how to invoke it correctly.

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