get_findings

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It clearly conveys that the tool performs baseline comparison over a 28-day window and returns highlighted anomalies rather than raw numbers. It does not mention output format or side effects, but 'Returns' strongly implies a read-only operation and the behavioral details given are valuable.

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?

Two sentences deliver both the tool's core behavior and usage guidance with no filler. The key output categories are front-loaded, and the preference statement earns its place by helping the agent decide when to invoke this tool.

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 zero-input analysis tool, the description covers what it returns, the comparison basis, and the preferred usage scenario. It lacks an explicit output schema or example, but the enumerated finding types give sufficient context for an agent to understand the tool's role among many siblings.

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 tool has zero parameters and schema coverage is 100%, so there is nothing for the description to add about parameter meaning. Per the baseline for zero-parameter tools, a 4 is appropriate; the description does not need to compensate for any schema gaps.

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 states a specific verb ('Returns what stands out') and a clear resource ('user's stored history against their own 28-day baselines'). It enumerates concrete signals—resting heart rate elevation, sleep debt, HRV trend breaks, training load ratio—which separates it from sibling tools that return raw metrics. The preference statement further distinguishes it from raw metric retrieval 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 says to prefer this tool over reading raw metrics when asked how things are going. This gives a clear contextual trigger and an implicit alternative. It does not name specific sibling tools or list exclusion cases, but the guidance is actionable enough.

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