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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that the data is aggregated from 40+ retailers and is weekly, but does not clarify whether the operation is read-only (highly likely for a retrieval tool), whether results are limited to the Top 10 by default, or how risers/fallers are computed. The absence of annotations but a plain retrieval description makes a score of 3 appropriate – it is transparent about what it returns but lacks depth on behavior.

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?

One sentence, front-loaded with the primary purpose and scope, then the region list. Every word earns its place, no redundancy or filler.

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 retrieval tool with fully documented parameters, the description covers the essential context: what is returned (rankings, risers/fallers), the regional scope, and the data source. The output schema is absent, so the description does not need to explain return values, but the tool also lacks guidance on how this relates to get_market_movers or get_disc_ranking, which likely overlap. Slight gap in distinguishing from siblings prevents a 5.

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%, and the description adds context by mentioning 'Top 10' and regional values, which aligns with the limit and region parameters. However, it does not add much semantic nuance beyond the schema – e.g., what happens when limit is reduced, how risers/fallers interact with the limit, or whether region values are case-sensitive. Baseline 3 is correct since the schema already documents both parameters well.

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 provides a specific verb ('Retrieve'), a specific resource (weekly disc golf retail sales rankings), and precise scope (Top 10, top risers/fallers by region). It also names the data source (40+ worldwide retailers), which distinguishes it from sibling disc-related tools that likely focus on individual discs or market movers.

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 is clear about what data the tool returns and specifies the region options, but it does not explicitly state when to use this tool versus the sibling tools like get_disc_ranking or get_market_movers. The context is implied (weekly rankings vs possibly daily rankings or individual disc details), but no exclusions or alternative routing are given.

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