List Electric Vehicles

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

Annotations already mark the tool as read-only, so the description need not restate safety. It adds useful behavioral context by naming the source database, the output fields, and the available filters. It omits details like pagination or ordering, but for a read-only list tool this is not a critical gap.

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 sentences front-load purpose and return values, then give the downstream workflow and filter options. Every sentence earns its place, and there is no redundant or filler wording.

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?

With two optional parameters and no output schema, the description provides the essential operational knowledge: what the tool lists, what fields are returned, how to use those results with calculate_ev_route, and how to filter. It is complete enough for an agent to select and invoke 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%: both 'make' and 'search' already have clear descriptions and examples in the schema. The description merely restates 'filter by make (brand)' and 'search by model name,' adding no new parameter meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 opens with a specific verb and resource: 'List available electric vehicle models from the ANWB database.' It names the exact return fields (car IDs, make, model, version, battery information) and points to calculate_ev_route as the downstream consumer, which clearly distinguishes it from the route-planning sibling tools.

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 gives explicit usage context: 'Use the car ID with calculate_ev_route to plan an EV route.' It also explains the optional filters. It does not enumerate when not to use this tool or explicitly compare it to alternatives, but the workflow guidance is clear.

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