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

Annotations already declare readOnly, idempotent, and non-destructive behavior Signals, so the description doesn't need to repeat those. It adds valuable behavioral context by detailing the exact nature of the output (named Solgar UK recommendations with rationale, health claim status, price, link), and notes that where no GB-authorised claim exists, a research-context note is provided, which is beyond what annotations offer.

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 concise and front-loaded: it opens with a clear trigger ('Call this when...'), then explains the output in a single sentence, and ends with input guidance. Every sentence adds necessary information without redundancy, and the structure is efficient for an agent to parse quickly.

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?

Despite lacking an output schema, the description thoroughly explains the return content, covering the rationale, claims, price, and link. It also specifies how to handle missing claims. The tool is relatively simple with only two parameters and no nested objects, so the description is sufficient for an agent to call it correctly, though the inclusion of an output schema could have made it even more 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 schema provides 100% description coverage, fully documenting both parameters (topic and concern) with their enums and plain-word guidance. The description adds minimal extra meaning beyond what the schema already provides, but it does indicate that the concern parameter can be used to route to a topic, which is a slight addition. The baseline of 3 for full coverage 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's purpose: it provides specific supplement product picks from HerStack's Solgar UK recommendations, including formulation rationale, health claims, pricing, and links. It distinguishes itself from siblings by focusing on product picks rather than claims, evidence, or general guidance, and it specifies the output contents, making its unique role clear.

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 tells the agent when to call this tool: when the user wants specific supplement product picks for a topic. It also provides guidance on how to provide input, either via a specific topic or a plain-word concern, and references alternative tools like search_guidance when the topic is unknown, offering clear routing guidance.

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