get_trend

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

With no annotations, the description carries the behavioral burden and does disclose the core behavior: one metric, weekly averaging, trailing N days. However, it is silent on how trend direction is determined, missing-data handling, and whether weeks are calendar-aligned — details an agent might need.

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?

One sentence conveys the computation, scope, and motivating use case with concrete examples. Every clause earns its place and the key constraint ('ONE') is front-loaded.

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 low-complexity, two-parameter tool with an output schema, the description plus schema is sufficient for an agent to invoke it correctly. It lacks explicit guidance on which sibling to choose instead, but the stated use case makes the selection path reasonably clear.

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?

period_days is already explained in the schema, and metric's enum values are largely self-explanatory; the description reinforces that exactly one metric is selected. This adds some meaning but does not materially compensate for the metric parameter lacking its own schema description.

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 concrete computation — weekly averages of a single recovery metric over a trailing window — and frames it around a clear question ('trending up or down?'). It distinguishes itself from broader summary/daily sibling tools without being a tautology.

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 a clear use context: answering whether HRV, resting HR, or sleep is trending over time. It does not name sibling tools or state when not to use it, so it stops short of a 5.

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