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

Annotations already declare readOnly/idempotent/non-destructive. The description adds the genuinely non-obvious behavioral fact that results are summed statistical weights, not raw case counts, which prevents misreading magnitude — a real value-add beyond the 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?

Front-loaded with the core action and metric before the example phrasings and optional age narrowing. The quoted example queries earn their place as intent anchors, though the sentence is dense and could be split for scanability.

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 so return format needn't be explained, defaults for year and limit are documented in the schema, and the description covers the ranking semantics that an agent actually needs to call it correctly.

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 coverage is 100%, so the baseline is 3; the description goes slightly further by giving a concrete interpretation of age_range ('0-4' for products that injure young children most), which explains what narrowing means in practice rather than just restating the enum.

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?

States a specific verb and resource ('Rank consumer products') plus the exact ranking metric ('national WEIGHTED emergency-department injury estimate for one year'), and names the sibling neiss_injuries, making clear this is the ranking view rather than the case-listing view.

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?

Embeds natural-language query phrasings ('what injures people the most', 'top products by ER visits') that map directly to user intent, and notes it shares neiss_injuries' methodology. It stops short of an explicit 'use X instead when Y' rule, so it is clear but not fully routing.

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