pandascore_series

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds a valuable caveat that the return shape is from vendor docs and unverified, and notes the authentication requirement. This goes beyond annotations, though it does not disclose pagination behavior beyond what the schema already states.

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 with brief segments for definition, return shape, caveat, example, and auth. Every sentence serves a purpose and there is no filler. The warning about the unverified shape is essential context, and the example is practical.

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 simple listing tool with no output schema, the description provides the return shape, an example, authentication details, and a reliability caveat. It lacks an explicit statement about behavior when no filter is applied, but the schema defaults and example make the expected behavior fairly clear.

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 descriptions cover 100% of parameters, yielding a baseline of 3. The description's concrete example (filter_videogame: 'lol') clarifies the expected slug format, which adds meaningful value beyond the schema's vague 'Title slug'. This justifies a 4.

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?

Description clearly identifies 'Series' as a league's seasonal editions and provides the return shape, making it evident that the tool retrieves series data. However, it lacks an explicit action verb like 'List' or 'Fetch', and does not directly differentiate from sibling pandascore tools (e.g., pandascore_tournaments), so it falls short of a top score.

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 example with filter_videogame implies a usage scenario, but there is no explicit statement about when to use this tool versus alternatives like pandascore_tournaments or pandascore_matches. No when-not-to-use or alternative tool references are provided, leaving usage guidance solely implied.

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