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

Annotations already cover safety and idempotency, and the description adds non-obvious behavioral context: the count is involvement, not causation, and unknown makes fail with a clear error naming valid makes rather than returning an empty success. This is exactly the kind of semantic and failure-mode context annotations cannot provide.

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 front-loaded with purpose, then immediately gives invocation modes and a critical caveat. Every sentence adds value, with no repetition or filler.

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 read-only query tool with full schema coverage and no output schema, the description covers the data source, ranking behavior, parameter interaction, semantic caveat, and error behavior. Nothing material is missing for correct selection and invocation.

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, but the description adds meaningful interaction semantics: year alone ranks top makes, while make plus year scopes to one make across loaded years. It does not add much about limit beyond the schema, so it is strong but not exhaustive.

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 states a specific resource and scope: vehicle makes involved in fatal crashes nationwide for a given year from NHTSA FARS. It clearly distinguishes this from generic vehicle-make tools by tying the data to fatal-crash involvement and FARS.

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 explicitly explains the two invocation modes: pass year alone for top makes ranked by involvement count, or pass make to get one make's counts across loaded years. It does not name sibling alternatives or state when not to use this tool, which keeps it below the top score.

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