list_supplements

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 by structured data. The description adds useful behavioral context: default filtering behavior, how to request history, and the full list of returned fields. This goes beyond annotations without contradicting them.

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 well-structured and front-loaded with the core purpose, followed by concise parameter inference guidance and a clear list of return fields. Every sentence adds value, and the use of labeled sections ('INFER — do not ask') makes it easy for an agent to parse. Nothing feels redundant or wasted.

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 list tool with two optional enum parameters and an output schema, the description is complete. It covers when to use the tool, what each parameter means, how to handle ambiguous matches, and what fields are returned. There is no missing information an agent would need to invoke this tool correctly.

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?

Although the input schema covers both parameters 100%, the description adds significant extra meaning. It defines the inference rules, explains the default 'active' filter, clarifies when to use 'all' vs 'historical', and specifies that omitting category returns both types. This is exactly the kind of parameter guidance that helps an agent choose values correctly without asking the user.

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 opens with a specific verb and resource: 'List the user's medications and supplements.' It clearly distinguishes itself from the sibling manage_supplement by explaining that list_supplements is for reviewing what the user takes, not for managing individual items. This lets an agent immediately know what the tool does and how it differs from related tools.

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 explicitly states when to use the tool: when the user asks what medications/supplements they're taking, asks to review their stack, or needs an id after an ambiguous manage_supplement match. It also explains that manage_supplement can resolve items on its own, so list_supplements is not a required prerequisite. This is strong, actionable routing guidance.

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