get_user_risk_factors

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

No annotations are provided, so the description bears the full burden of behavioral disclosure, and it only states a 'get' plus the field list. It does not explain how 'calculated risk level' is derived or whether it is computed on demand vs precomputed, does not say what happens when the user's profile has missing fields (e.g., sun exposure, family history), and gives no caveats that would matter for a medical decision-support tool.

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 tight sentences with zero wasted words: the first carries the technical contract (verb, resource, content), the second says when to use it. The 'including' wording also signals a non-closed factor list without bloating the text.

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?

With no output schema and no annotations, the description is the only shape for the return object; the field list is helpful but incomplete — the scale/format of 'calculated risk level' is undefined and edge-behaviors (unknown user, incomplete profile) are not addressed. For a single-parameter lookup the input contract is fully self explains, so it's invokable, but the output disposition is left to runtime discovery.

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?

Scalar schema description coverage is 100%: userId is already documented as 'the user's unique identifier,' so the description adds no param-level info and doesn't need to. Baseline 3 applies because the schema fully roughly covers the only parameter and there is no secondary param ambiguity.

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 has a specific verb resource pair — 'Get a user's skin cancer risk factors' — and enumerates the returned content (skin type, family history, sun exposure habits, calculated risk level), so the aim is unambiguous. The 'a user's' phrasing implies a per-user scope that differs from condition-level sibling tools (e.g., get_condition_risk_factors), but it never names/contrasts any sibling explicitly, so the distinction is left to inference.

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 last sentence 'Use this for personalized advice' offers a clear context where the tool fits — interactive user-advice flows — which is better than nothing. However, it names no alternatives (get_condition_risk_facters, assess_risk_from_factors, get_user_moles), no when-not-to-use conditions, and no decision rules among them.

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