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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safe read-only profile is covered. The description adds that the operation samples from named distributions, but it does not disclose determinism via seed, output size implications of count, or any limits. With annotations carrying the safety profile, this is adequate but not rich.

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?

The description is a single front-loaded sentence with no filler and the verb appears immediately. It is efficient, though it is a bare list rather than structured guidance, so it is not a model 5.

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 and parameter descriptions are complete, so the description need not explain return values or every parameter. It names the sampling distributions and is sufficient for invocation given the structured fields, though it leaves sibling-selection context thin.

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%, and the schema already documents all parameters including distribution-specific meanings such as mean/std for normal and n_trials/p for binomial. The description only repeats distribution names and uses 'randint' while the schema enum says 'random_integer', adding little beyond structured data; baseline 3 applies.

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 uses a specific verb, 'Sample', and enumerates the supported distributions (uniform, normal, exponential, binomial, poisson, randint), so the agent knows it generates random samples from those families. It does not differentiate this tool from sibling calculators such as calculator_random, calculator_normal or calculator_binomial, so it stops short of a 5.

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 when-to-use guidance, no comparison to alternatives, and no exclusions or prerequisites. The supported distribution list only implies usage; it does not help the agent choose this tool over calculator_random or the individual distribution calculators.

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