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

It adds meaningful context beyond annotations by disclosing the continuous-engine requirement and refusal behavior. However, annotations mark the tool destructiveHint=true, and the description does not explain what gets destroyed or what side effects a run has; with that strong annotation, more disclosure would be expected.

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: the first front-loads the core operation and output shape, the second states a key limitation. No filler or repetition of schema content.

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 an 8-parameter tool without an output schema, the description covers the operation, output as a grid, and a critical refusal case. It could clarify what destructiveHint=true means in practice, but the agent can otherwise call the tool correctly using the schema.

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 100%, so the schema carries the parameter burden. The description reinforces that param_x/param_y are transition rates and observable fills the grid, but adds no format or edge-case details beyond what the schema already states.

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 opens with a specific verb+resource ('Two-rate grid for a stored model') and specifies the exact mechanics: vary two transition rates, run each combination, return final observable value as a grid. This clearly distinguishes it from siblings like sim_scenario or sim_optimize even without opening their 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?

The description gives an intended use case ('which regime of arrivals × restock keeps the queue empty') and a clear exclusion: models with a schedule or gate are refused with the reason. It stops short of naming alternative tools for those cases, but the refusal condition is explicit.

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