recommend_supplement

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

With no annotations, the description carries the full burden. It discloses the main behavior: returning ranked products with clinical evidence, dosing, cost-per-dose, and purchase links. This makes the tool's read-only nature and output format clear, though it could mention edge-case behavior (e.g., invalid inputs).

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 concise sentences front-load the purpose and then detail what is returned. No wordy or redundant explanations.

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 description covers the core function and return format, and the schema is rich. It does not explicitly differentiate from siblings at a usage level, but given the simple nature of the tool and the clear purpose, it is sufficiently 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% coverage with detailed descriptions for both parameters, including examples and the note about unrecognized supplement names. The description adds little beyond the schema, so it meets but does not exceed the baseline.

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's function: 'Get evidence-based supplement recommendations for a specific condition.' It specifies the verb, resource, and context, and it is distinct from sibling tools like compare_forms and get_dosage, which focus on different aspects.

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 clear context for when to use the tool ('for a specific condition') and mentions the ability to omit condition for a general recommendation. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous enough for an agent to infer when to use this tool over siblings.

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