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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds useful behavioral context: filtering by sex/age when relevant, the contents returned (high/low implications, retest cadence, testing instructions), cited sources, review date, and the educational precedence caveat. No contradiction with 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 one information-dense sentence with no filler, repetition, or vague wording. It front-loads the core purpose and then adds distinct facts: marker count, filtering behavior, output contents, source/review information, and the educational caveat.

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?

With no output schema, the description does well by explaining what the agent can expect: reference range, high/low interpretations, retest cadence, how to get tested, cited sources, and review date. It is slightly incomplete in not addressing how to handle unknown markers or clarifying the optional pregnancy/postmenopausal inputs, but it is still sufficient for a simple read-only lookup tool.

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 only 20%, so the description must compensate. It does add meaning for age and sex ('filtered by sex and age when they matter'), but it does not explain pregnancy or postmenopausal parameters, which are likely relevant optional filters. The marker parameter is already described in the schema, so the description only partially fills the coverage 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 names the verb and resource: lookup of a physician-reviewed reference range for a blood test marker. It adds scope (130+ markers), the filtering dimensions (sex and age), and the content categories returned, making it easy to distinguish from siblings like interpret_results or recommend_tests.

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 provides no explicit when-to-use or when-not-to-use guidance and does not name alternative tools. It implies an educational use case and notes that the user's report range takes precedence, but it leaves tool selection among siblings to inference.

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