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

With no annotations, the description carries the full burden, and it does add real value by disclosing what the response contains (defect, consequence, remedy, units affected) since there is no output schema. However, the cryptic 'PRO.' prefix is never explained — the subscriber-token requirement only surfaces in the schema — and nothing is said about behavior for an unknown recall number, error modes, or rate/quota limits.

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?

A single front-loaded sentence plus a two-character prefix; the purpose and the payload are stated with no filler. The one inefficiency is the unexplained 'PRO.' token, which costs a word without conveying meaning to the agent.

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 two-parameter, no-annotation, no-output-schema tool, the description covers the most important gap — what comes back — which is good. It still leaves the auth/PRO gating, recall-number format, and failure behavior unaddressed, which is thin for a tool with zero structured guidance.

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 only 50%: access_token is documented in the schema, while recall_number has no description at all. The description partially compensates by qualifying it as a Transport Canada recall number, but gives no format or example of what such a number looks like, so an agent still has to guess the expected shape.

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 names a specific verb and resource ('Full Transport Canada recall details for a recall number') and enumerates the returned fields (system, units affected, defect, consequence, remedy). The phrase 'for a recall number' implicitly contrasts it with the list-style siblings (vehicle_recalls, new_vehicle_recalls), though it never names one explicitly.

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?

Usage is only implied: the singular 'a recall number' suggests a follow-up detail lookup after a list tool returns an identifier, and the 'PRO.' prefix hints at a paid/subscriber tier. There is no explicit when-to-use, when-not-to-use, or named alternative among vehicle_recalls, new_vehicle_recalls, or fleet_check.

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