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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it returns price, payment location, and an order link, and it implies a nearest-lab ranking. It does not disclose details like whether results are sorted by distance or whether availability varies, but the annotations lower the burden.

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 a single, information-dense sentence that front-loads the core purpose and includes a helpful example query. It is slightly long but every clause earns its place; the example query at the end is useful for an agent.

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 lookup tool with two well-documented parameters and no output schema, the description covers the main inputs, the use cases, and the kind of output (price, payment location, order link). It does not specify the output format or sorting, but the annotations and schema cover the rest. The tool is simple enough that this is nearly 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 description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds a little context by listing the test types in prose and noting the default, but it does not add meaning beyond the schema's own descriptions. Baseline 3 is appropriate.

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 states a specific verb ('find'), a resource ('Hera partner labs near a US ZIP code'), and the exact use cases (semen analysis, post-vasectomy check, etc.). It also includes a concrete example query ('where can I get a sperm test near me'), which makes the tool's purpose unmistakable and distinguishes it from siblings like get_lab.

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 clearly indicates when to use the tool: for location-based lab searches near a ZIP code, and gives a natural-language trigger. It does not explicitly name alternatives or say when not to use it, but the sibling context (get_lab, hera_facts) and the explicit 'near a ZIP code' scope make the usage context clear.

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