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

With no annotations, the description fully discloses behavioral traits: real-time data, presence of buy_url for non-motor, deliberate omission for motor, and the mandatory post-quote workflow. It also reveals that motor offers include a to_buy field to collect customer details. This is transparent about the tool's side effects and obligations.

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 dense yet efficient. It opens with the core purpose, then delivers the critical motor-workflow exception, and finally lists rating inputs per product type. Every sentence carries essential information with no filler. Despite its length, it remains well-structured and front-loaded.

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 the tool's complexity (10 parameters, 4 product types, no output schema), the description covers all necessary aspects: real-time quote retrieval, buy_url for most products, the motor exception with required follow-up, and the specific parameters needed per product. It also references the to_buy field without relying on an output schema. This makes the description self-sufficient for correct tool 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?

The schema already provides 100% coverage with parameter descriptions. The description adds value by consolidating which parameters are required for each product type (e.g., auto → sum_insured + cover_type) and clarifying the meaning of sum_insured for different lines. While it largely repeats schema info, the structured mapping aids correct usage beyond the raw schema, justifying a score above baseline.

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's function: retrieving real-time insurance premiums across multiple partner insurers in NGN. It specifies the resource (partner insurers) and the action (get premiums), and differentiates from sibling tools like get_buy_link by explicitly describing when that tool is needed. The mention of product types further clarifies scope.

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 provides explicit usage guidelines, including when to use this tool (to get quotes) and the required follow-up for motor quotes (must ask for vehicle/address/NOK details and call get_buy_link). It also explains how rating inputs vary by product type, effectively guiding the agent on parameter selection. This distinguishes it clearly from get_buy_link and other siblings.

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