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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds real operational context the annotations lack: results are ordered newest first, matching is conjunctive (every word must appear), and the corpus is English-language DVSA text. Pagination/result limits are not disclosed.

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 sentences, front-loaded with the core behavior before the examples. The example keywords (

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 search tool with no output schema, the description covers scope, matching semantics, language, ordering and a usage scenario. It omits result-count limits, pagination and how matches on different fields are weighted, which an agent would want before relying on 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 coverage is 100%, so both parameters are already documented ('words that must all appear', 'only recalls launched on/after it'). The description reinforces the AND semantics and date scoping but adds no syntax beyond the schema, so the baseline 3 applies.

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?

States a specific verb (keyword search) over a named resource (all served DVSA recalls) and enumerates the searched fields (make, model, concern, defect, remedy). The 'all served / cross-make' framing implicitly distinguishes it from the sibling uk_recalls_for_model, which is model-scoped.

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?

Gives a concrete use case ('cross-make questions such as recent EV battery fire recalls in the UK'), which tells the agent when this tool fits. It does not explicitly name uk_recalls_for_model as the narrower alternative or state exclusions, so it stops short of full routing guidance.

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