nhtsa_model_years

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

Annotations only declare readOnlyHint=true; the description adds behavioral context by stating that it lists years with recalls or complaints and by giving the 1949–present date range for recalls. This goes beyond the structured annotations, though it does not describe return format or pagination.

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 short, front-loaded sentences with zero filler. Every sentence earns its place: what the tool does, how to set the key parameter, and when to use it.

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 simple read-only listing tool with one param and no output schema, the description conveys purpose, parameter behavior, and use case. It could mention the exact output shape or empty-result behavior, but that is not strictly necessary for an agent to invoke it.

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 already documents issue_type enum (r/c) with descriptions at 100% coverage. The description adds extra semantic value by clarifying usage with concrete examples and the recall date range, helping the agent map the parameter to real-world meaning.

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?

Description opens with a specific verb and resource: 'List model years that have recalls or complaints in the NHTSA database.' This clearly differentiates from sibling NHTSA tools like nhtsa_recalls (which return recall records) and nhtsa_makes/models (which return other catalogs).

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?

Provides explicit direction on when to use it: 'Useful for discovering available data before querying' and how to choose issue_type ('r' for recalls, 'c' for complaints). It does not explicitly name alternative tools or exclusions, but context is clear enough.

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