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

Beyond annotations, the description explains that whitespace-separated filter tokens must match code, name, or definition case-insensitively. It also states that filtering covers the complete dictionary before sorted pagination, which clarifies matching and pagination 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?

The description is front-loaded and compact, moving from core purpose to filter semantics to pagination behavior to next-step usage. Each sentence contributes useful information without repetition.

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?

The tool has annotations, full schema descriptions, and an output schema, so return-value details are not needed. The description sufficiently covers purpose, filtering behavior, pagination scope, and how to use the returned codes.

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 schema already documents parameters well. The description adds meaningful semantics for the filter parameter, including whitespace-token matching against code, name, and definition, plus the blank-filter browse behavior and pagination scope.

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 uses a specific verb and resource: it finds parameter codes supported by a community and temporal resolution. It also distinguishes the tool as a discovery step by saying returned codes should be passed to a producing tool.

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?

It gives clear usage guidance for the filter: blank filter browses all codes, and returned codes should be passed to a producing tool. It does not explicitly name sibling alternatives such as list_reference, but the context is otherwise clear.

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