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

Beyond the readOnly/idempotent annotations, the description discloses the counting methodology (one per serial number by filing date), the scope distinction from fiscal-year statistics, and the data freshness caveat that recent periods grow as late records arrive. This gives the agent important expectations about result stability and interpretation.

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 somewhat long but well structured: core behavior first, example questions second, caveats last. Every sentence carries useful information, and the most important scoping statement is front-loaded, though the first sentence is dense and could be split.

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 aggregate tool with no output schema, the description covers the return concept (periods, splits, change, data_through), counting rules, and data freshness. It doesn't detail the exact output shape, but it provides enough about return semantics for an agent to invoke and interpret the result correctly.

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 coverage is 100%, so the baseline is 3, but the description adds genuine semantics: counts are based on filing date on the USPTO record, daily grouping covers at most about a year, and the meaning of returned periods is clarified. This goes beyond the schema's date-format and enum descriptions.

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 states a precise action and resource: counts U.S. trademark applications across the whole register within a date range, grouped by year/month/day. It distinguishes itself from attribute-based counting by explicitly saying it is not class counts and covers the whole register, so an agent can tell it apart from siblings like count_trademarks_by_attributes.

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?

Gives concrete example questions ('how many trademark applications were filed in 2025 and how that compares with 2024') and clear scope constraints: whole register, calendar periods, not USPTO fiscal-year statistics, not class counts. It does not name an alternative tool explicitly, but the exclusions effectively route an agent away from attribute-based or fiscal-year tools.

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