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

Annotations provide readOnlyHint: true, so the agent knows this is a safe read operation. The description adds value by explaining the tool's role as a lookup/reference, which implies no side effects. It also mentions partial match support and pagination parameters in the schema, but the description itself doesn't disclose behaviors like rate limits or data freshness. Given the annotation covers safety, the description's additional context on discovery is useful, but it doesn't delve into specifics of the data source or any quirks. With annotations present, a 4 is justified as the description complements rather than repeats them.

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 a single, two-sentence paragraph. It is concise, with the core purpose stated upfront and then usage scenarios. Every word adds value: it names the tool's function and provides concrete examples of when to use it. No filler or redundant information. This is an exemplar of conciseness for a tool description.

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 the tool has a rich input schema (6 parameters, one with enum) and an output schema (as indicated by 'has output schema: true'), the description doesn't need to explain return values or parameter details. The description is complete for the tool's purpose: it tells the agent what the tool does and when to use it. The schema handles parameter specifics, and annotations handle safety. The only slight gap is that it doesn't explicitly mention pagination behavior, but the schema covers that (offset/limit). Overall, the description is sufficient for an agent to use the tool 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 description coverage is 100%, meaning each parameter has a description. The tool description itself doesn't repeat parameter details, but it explains the overall purpose (e.g., 'find correct make/model spelling') which indirectly clarifies how parameters like 'make' and 'operation' are intended to be used. Since schema already documents each parameter, the description adds context by framing the tool's use case, which helps an agent understand parameter interactions. This goes slightly beyond baseline 3 because it clarifies the high-level semantics of the operations.

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: to look up valid makes, models, and vehicle types in NHTSA's database. It uses a specific verb ('look up') and resource ('NHTSA's database'), and lists concrete use cases. While it doesn't explicitly differentiate from siblings, the sibling names (e.g., nhtsa_decode_vin, nhtsa_get_safety_ratings) suggest different domains, and the description's focus on lookup/discovery distinguishes it from those. However, it doesn't explicitly state what it is NOT, so it falls short of a 5.

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: 'Use to resolve ambiguous vehicle names, find correct make/model spelling, or discover what models a manufacturer produces.' This gives specific scenarios for usage. However, it doesn't explicitly mention alternatives or conditions where another tool should be used instead, which prevents a 5. The guidance is clear enough for an agent to decide, but it lacks explicit exclusions.

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