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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuine interpretive context beyond structured fields: passing does not prove a dataset exists and inconsistency does not establish fraud, which shapes how an agent should report results. It still does not say what the check actually returns or which quantities drive a failure.

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, front-loaded with the operation and followed by the crucial interpretation caveat. Every sentence earns its place; nothing is redundant with structured fields.

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 six-parameter, no-output-schema tool, the description covers purpose and interpretation but leaves gaps: no explanation of what a result looks like (pass/fail verdict, p-value), no guidance on n or the bounded-scale parameters, and no failure-mode detail. Adequate but incomplete.

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%, so the description must carry parameter meaning; it partially does by naming means, sample deviations, rounding, and bounded integer observations (mapping mean, sd, decimals, min_value/max_value). It never mentions n, the second required parameter, nor the meaning of decimals/min/max defaults.

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 names a specific verb (apply checks) and resource (GRIM/GRIMMER consistency checks on rounded means and sample deviations of bounded integer observations), which is precise enough that an agent can tell it performs statistical consistency auditing rather than any sibling operation. Siblings are all unrelated domains, so no differentiation is needed.

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?

Usage is implied by 'apply necessary GRIM/GRIMMER checks to rounded means and sample deviations' – i.e., call this when you have a reported mean/sd/n from a bounded integer scale. However, there is no explicit when-to-use vs when-not guidance, no mention of prerequisites, and no routing to alternatives.

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