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

No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about cost, side effects, whether the call is deterministic, or what happens on invalid model/function values. Most critically, both required parameters are free-form strings with no enum, and the description offers only one example pair without indicating where valid values come from (presumably describe_model or list_models).

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?

It is a single short sentence with the example front-loaded, so there is no wasted wording. But the brevity is achieved through under-specification rather than efficiency; the space saved is exactly the information an agent needs.

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?

An output schema exists, so return values need not be explained, but that is the only thing in this tool's favor. With zero annotations, 0% schema description coverage, and two free-form required parameters, the description should explain valid value sources and the role of `inputs`; it does none of that.

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 description coverage is 0% across all three parameters, so the description must compensate and largely does not. It illustrates `model` and `function` with a single example each but never explains the `inputs` object, which has an open-ended additionalProperties schema and defaults to null — the highest-risk parameter is entirely undocumented.

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 gives a verb ("Run") and an object ("a model's extra calculation"), plus a concrete example pair (model='variable_annuity', function='nested') that makes the intent partially graspable. However, "extra calculation" is undefined jargon and nothing distinguishes it from siblings like price_model or describe_model, so the agent cannot tell what kind of computation this actually performs.

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?

There is no statement of when to use this tool versus price_model or describe_model, and no prerequisites or exclusions. The single example implies a usage pattern only by inference; an agent has to guess the selection rule.

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