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

Annotations already declare read-only and non-destructive. The description adds the measurement source ('dates stated in the decisions'), the output format (median years, counts), and the crucial caveat that it is descriptive rather than predictive—valuable context beyond annotations.

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?

Three concise sentences: the first states the metric, the second the output, and the third the non-predictive caveat. Every sentence earns its place, and the main purpose is front-loaded.

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?

Given a single optional parameter, no output schema, and a read-only analytical tool, the description covers the calculation basis, categories, output summary, and non-predictive nature. It is sufficiently complete for an agent to invoke and interpret the tool.

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?

The sole parameter 'guideline' is fully documented in the schema with its letter-to-category mapping, and schema coverage is 100%. The description adds no further parameter detail, so a baseline of 3 is appropriate.

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 clearly states the tool computes the time between most recent conduct and decision for specific incident-type concerns, reporting median years by decision outcome. It is specific and not a tautology, and the 'never a prediction' caveat further clarifies its analytic role.

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 specifies the exact incident-type scope and the boundary that it is descriptive, not predictive, which implies when to use it. However, it does not explicitly name alternative tools or exclusions beyond the prediction caveat.

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