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

Annotations already establish that this is a safe, read-only, idempotent search. The description adds useful data-behavior context: results include the grade rationale, PubMed-linked reviews/trials, compounds and body structures, while doses are deliberately omitted.

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 front-loaded with the use case and includes only relevant information. The opening sentence is dense and could be split, but the remaining sentences and example earn their place.

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?

There is no output schema, so the description carries the burden of explaining returns; it does so by enumerating grade, rationale, PubMed-linked evidence, compounds, body structures, and the atlas page. It also states important exclusions such as omitted doses and non-medical-advice status.

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%, so the schema already documents both optional parameters. The description still adds value by mapping the ladder phrase "evidence of no benefit" to the schema enum value "against" and by giving an example query argument.

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 names a specific resource (conditions on an evidence ladder) and a clear use case ("does cannabis help with ..."). It is easy to distinguish from compound or trial lookup tools, but it does not explicitly contrast itself with sibling tools such as search, find_studies, or list_trials.

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?

It gives explicit usage guidance via the "Use for 'does cannabis help with ...'" framing and rules out diagnostic or dosing use. However, it does not say when to use alternatives like find_studies or list_trials instead.

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