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

The annotations already declare that this is a read-only, non-destructive, idempotent operation, so the safety profile is covered. The description adds meaningful behavioral context beyond the annotations by clarifying what the checks examine and by warning that passing is not proof of a dataset and inconsistency is not evidence of fraud.

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 three sentences, front-loads the core operation, and avoids repetition. It is appropriately sized for the tool, though the abstract phrasing could be slightly more structured for an agent parsing required inputs.

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 tool with six parameters, no output schema, and zero schema description coverage, the description is incomplete on operational details. It provides an important interpretive warning but does not explain input requirements, parameter usage, or what a result consists of.

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 compensate for the six undocumented parameters, but it does not. It hints at means and sample standard deviations and bounded integer observations, but it never explains parameters such as n, decimals, min_value, or max_value, leaving most parameter meaning unspecified.

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 specific verb ('Apply') and a specific resource ('GRIM/GRIMMER arithmetic consistency checks to reported statistics'), which is clear enough to distinguish this tool from unrelated siblings. It does not explicitly name or differentiate itself from any sibling tool, so it falls 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?

It implies the tool is used for reported statistics with bounded integer observations and rounded means/sample standard deviations, but it does not state when to prefer this tool over alternatives or when not to use it. The caveat about passing filters not proving a dataset exists adds interpretive context but not operational routing guidance.

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