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

With no annotations, the description carries the full burden of behavioral disclosure. It adds key facts: zero count means no match in the ingested subset, a max 50 result limit, and a cost of $0.005 USDC per call via x402. It does not mention authentication or rate limits, but the disclosed behaviors are useful and go beyond what the schema provides.

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 the purpose and return contents, then adds usage context, zero-count behavior, and cost. Every sentence contributes information an agent needs; it is slightly long but not bloated. The structure is logical, with the most important facts appearing first.

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 no output schema and four parameters, the description fully covers what an agent needs: what is returned (id, summary, fault codes), the max result count, how to query (make/model/year or code), when to use it (after dtc_lookup), and what a zero count means. The cost disclosure also helps with decision-making. Nothing critical is missing for correct 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 schema already documents each parameter's type and example. The description adds meaning by clarifying the parameter usage pattern: 'Query by make/model/year, or by fault code' and noting that 'code' is optional and 'make' is required unless code is given, which supplements the schema's flat list. This is above the baseline for fully covered schemas.

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 returns NHTSA Technical Service Bulletins with a specific verb ('Returns') and resource, and distinguishes them from safety recalls. It also names the query methods (make/model/year or fault code), making its purpose unambiguous and distinct from the sibling tools like vehicle_recalls.

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 explicitly says 'Use this after dtc_lookup when you want the manufacturer's documented fix,' providing a clear condition and sequence. It also explains the query methods (by make/model/year or by fault code). However, it does not explicitly state when NOT to use it or contrast with vehicle_recalls or vin_decode, so it stops short of full exclusion guidance.

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