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

Beyond the readOnly/idempotent annotations, the description discloses critical behavioral facts: cars are privately owned, payment flows to the owner, instant confirmation differs from owner confirmation, price_day:null is normal, booking_link must be preserved verbatim, and phone/address/licence plate must never be invented. This is exactly the kind of context annotations cannot convey.

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?

Though long, the description is sectioned, front-loaded with purpose, and every paragraph carries a distinct operational rule. The bold section labels and explicit warnings make the density navigable. Nothing feels padded or redundant.

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 16-parameter tool with no required fields, this description covers usage scope, data model, pricing semantics, mandatory link handling, privacy constraints, and coordinate precision. With an output schema present, return-value details are not needed. An agent has everything required to invoke the tool safely and 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 coverage is high (88%), so the baseline is 3, but the description adds real semantic value: it explains the meaning of price_day:null, that price_min keeps cars without a published rate, that coordinates are approximate for radius searches, and how pickup/return dates frame total_eur. It doesn't enumerate every parameter, but it compensates meaningfully beyond the schema.

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: 'Search RENTAL CARS on HotelsCasa by city, country or geographic radius,' and enumerates the key filter dimensions. It explicitly distinguishes cars from properties, so the agent can separate this from property-search siblings. This is a model of purpose clarity.

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 this tool only when the traveller asks about a car, never to answer an accommodation question.' It also explains the inventory model, which helps the agent decide when this tool is appropriate. It does not name sibling tools like get_vehicle or check_vehicle_availability, so some selection nuance is left to inference.

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