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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint true, and destructiveHint false. The description adds valuable context beyond annotations: dataset size, date range, and ongoing appending behavior. It explains VIN prefix semantics, which is non-obvious. No contradictions.

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 well-structured and front-loaded: it starts with the core action, provides dataset context, gives example queries, and explains a key feature (VIN prefix). Every sentence adds value without being overly verbose. Minimal waste.

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 7 parameters with 0 required and no output schema, the description is remarkably complete. It covers data scope, use cases, parameter guidance, and return behavior (individual records vs counts). The absence of output schema is mitigated by clear examples of what the tool answers.

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 100%, so baseline is 3. The description adds meaning by providing concrete examples (e.g., 'W1KAF4GB5SR257239' for vin) and practical use cases for parameters like expires_before and inspected_since. It explains the concept of VIN prefix as counting one model line, which goes beyond the schema's description.

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's purpose: looking up DC vehicle inspections by VIN or counting inspection volume over time. It distinguishes itself from sibling tools like dc_dmv_convictions and dc_dmv_offices by focusing specifically on inspections. The examples of queries it can answer leave no ambiguity.

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?

The description provides clear context on when to use the tool, including example questions and explanation of VIN prefix queries. It implicitly differentiates between individual record lookup and volume counting via the group_by parameter, but it lacks explicit 'when not to use' or direct comparisons with alternatives.

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