get_trend

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond them: the minimum-5-values threshold, the no_trend-with-reason fallback, and the restriction to approved values. It stops short of describing pagination or performance, but for a read-only statistical tool this is solid.

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?

Front-loaded with the core purpose and output shape, then routing guidance, then parameter notes. Dense but nearly every clause adds information; the parenthetical method name and unit glosses are justifiable, though the description is on the longer side.

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?

Output schema exists, so return fields need not be re-specified, yet the description still summarizes the result shape (direction, z, p-value, slope). Combined with usage routing, the 5-value precondition, and parameter meanings, nothing an agent needs to invoke this correctly is missing.

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 0%, so the description must carry the burden, and it does: type_code is explained as a catalog code with concrete examples (ldl, hemoglobin, vitamin_d) plus where to obtain it, and days is described as the window with its default meaning (~5 years). Both parameters gain meaning not present in the schema.

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?

States a specific verb+resource+method ('Statistical trend of one marker over time (Mann-Kendall test + slope)') and scopes it to 'approved values'. It also explicitly distinguishes itself from the sibling query_observations, so an agent can tell them apart without opening schemas.

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?

Gives explicit when-to-use ('Use for "is X going up/down"') and names the alternative for the contrasting case ('for the raw values use query_observations'). It also states the prerequisite (at least 5 values in the window) that determines whether the tool is even applicable.

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