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

Annotations already indicate read-only and non-destructive, so the bar is lower. The description adds meaningful behavior: 'Numbers are collected receipts and counted cargo — never announcements', clarifying data provenance and that it's fact-based rather than forward-looking. It also notes default-to-latest-month behavior, adding context beyond annotations.

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 dense but efficient: it front-loads the value proposition, then gives use cases, parameter usage, data caveat, and auth note in four sentences. Every clause serves a purpose, with no filler or repetition. The structure is logical and easy to parse.

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?

Given the tool's simplicity (2 optional params, no output schema) and rich annotations, the description covers the essential context: what data is included, how to use parameters, data source caveat, and default behavior. It doesn't detail the return format or what the 'detail' levels produce, but for a report-generating tool with no output schema, it's sufficiently complete for an agent to decide and invoke.

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 50%: 'month' has a description and pattern, while 'detail' has only enum values and default. The description clarifies 'month' format and default behavior ('pass month:"YYYY-MM" for history') but does not explain the meaning of 'answer', 'standard', or 'full'. With one parameter well-documented in schema and another only partially in description, the description partially compensates but leaves a gap.

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 ('Use for') and resource ('US trade last month'), enumerating exactly what the report contains: tariff bill comparisons, duty movements, gateway imports, and trade-war measures with Federal Register citations. This rich detail distinguishes it from sibling tools like query_series or tariff_story, making its purpose unambiguous.

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 explicitly provides usage triggers: 'what happened in US trade in June', 'any new tariffs this month', or opening a briefing. It also clarifies default behavior (latest complete month) and history mode via the 'month' parameter. While it doesn't name alternative tools or exclusions, the use cases are concrete and actionable.

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