get_specimen_requirement

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

With no annotations, the description carries the disclosure burden, and it does disclose meaningful constraints: the data is decision-support-only, not pre-submission storage, not validated for hospital deployment, and current official sources must be verified. It also warns against entering patient data. What it omits is response/pagination behavior, but output schema exists and the tool is a simple read.

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 short and the main action is front-loaded. The flag list and the patient-data warning are terse and somewhat cryptic (e.g., '=true' syntax), but each clause carries information and there is no 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?

Given the low schema coverage and one-parameter surface, the description could be complete, but it omits the accepted disease value format and doesn't route among the many sibling tools. The output schema plus safety flags cover return and usage constraints, so it is adequate but not fully complete.

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 0% and the single 'disease' parameter is not explained in the schema or description. The description implies the tool is queried by disease and that patient data must not be passed, but it does not state accepted values, format, or codes. That leaves a real 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 opens with a concrete verb-resource pair: 'Get CDC specimen rows,' which identifies the data source and broad action. It does not explicitly contrast with siblings like get_collection_method or get_transport_requirement, but the resource is specific enough to avoid obvious confusion.

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 boolean flags provide explicit context: decision_support_only, not_validated_for_hospital_deployment, and not_pre_submission_storage tell an agent when the result is and isn't appropriate to use, and the Chinese instruction forbids patient data as input. It does not name sibling alternatives, so it stops short of full routing guidance.

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