Get lab test results

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

With no annotations provided, the description carries the behavioral disclosure burden. It does describe the returned fields (test type, pass/fail, measured level, testing lab) and clarifies the ID requirement, but it does not mention read-only behavior, error cases, or pagination. It is adequate but not comprehensive.

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?

Two sentences contain exactly the needed information: the action, the critical ID caveat with its resolution path, and the returned fields. Every sentence earns its place and the key constraint is front-loaded.

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 there is no output schema, the description lists the return fields sufficiently. It covers the required parameters, the prerequisite for resolving package IDs, and the tool's purpose. Minor gaps like potential multiple results or authentication remain, but for a read-only fetch tool this is reasonably 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 100% for both parameters, so the schema already documents their types and defaults. The description adds one important semantic distinction beyond the schema: the packageId is numeric and must not be confused with the tag label, which requires resolving via get_package first. This adds real value beyond structured data.

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 ('Fetch'), a clear resource ('lab test results'), and a precise input ('numeric package ID'). It explicitly clarifies that the ID is not the tag label, distinguishing this from tag-based lookups and preventing common misuse.

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 gives a clear prerequisite: use get_package first to resolve the numeric package ID, steering the agent away from tag labels. It does not explicitly state when to prefer this over sibling list tools, but the context is clear enough for a simple fetch operation.

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