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

With no annotations, the description carries the full burden. It discloses that results are evidence-graded and include dosages, which are key behavioral traits. However, it does not mention ordering details, potential lack of results, or any limitations beyond what is in the parameter schemas.

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 two sentences with no filler. It front-loads the tool's purpose and provides a concise output summary, earning every word.

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 is a simple retrieval query with fully self-describing parameters and a clear return type (evidence-graded recommendations with dosages). No output schema exists, but the description covers the key output semantics. It could be slightly enhanced by explaining the evidence grading scale or explicitly distinguishing from the biomarker sibling, but it is generally 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?

The input schema provides 100% description coverage for all parameters, including defaults and allowed values. The tool description adds minimal parameter meaning beyond examples that already appear in the condition parameter description. 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 clearly states the tool finds supplements for a health condition or goal, with specific examples like 'sleep' and 'joint pain'. This distinguishes it from siblings such as get_supplements_for_biomarker, which target biomarkers instead.

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 establishes a clear context for use (when you have a health condition or goal) and mentions the evidence-graded output, but it does not explicitly name alternative tools or state when not to use it. It implies usage rather than providing exclusions.

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