get_quotePrice an order (package_code, quantity, optional promo code) exactly as checkout would: returns subtotal, discount, and the final total in USD cents, plus the promo status. Purely informational — no order is created.
| Name | Required | Description | Default |
|---|---|---|---|
| quantity | No | Units to buy (default 1, max 10). | |
| promo_code | No | Optional promo code to apply. | |
| package_code | Yes | The plan's package_code from search_plans. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While annotations already provide readOnly and idempotent hints, the description adds detail about return values (subtotal, discount, total in cents, promo status) and confirms no side effects. This adds behavioral context beyond the annotations.
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 two sentences with no wasted words. It front-loads the core purpose and then provides important behavioral details efficiently.
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 no output schema, the description adequately lists return fields. It covers the essential behavioral aspects (pricing logic, no order creation) and the parameters are fully documented in the schema, leaving no gaps for an agent to understand correct 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?
Although schema coverage is 100% with parameter descriptions, the tool description reiterates the parameters' roles in the pricing operation but does not add significant new meaning 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 uses a specific verb 'price' and resource 'order', and clearly distinguishes from siblings by specifying it returns pricing breakdown exactly as checkout would. It also states it's purely informational, which differentiates it from order creation 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 tells when to use (to price an order exactly as checkout) and what it does not do (no order created). It does not explicitly mention alternatives or when not to use, but the context of siblings implies usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
All tools have distinct purposes: check_availability checks fulfillment, get_plan fetches details, get_quote prices orders, and search_plans searches the catalog. No overlap.
All tool names follow a consistent verb_noun pattern (check_availability, get_plan, get_quote, search_plans), making them predictable.
With 4 tools, the server is well-scoped for a catalog/quoting service. Each tool adds clear value without being too few or too many.
The tool set covers search, detail retrieval, availability, and pricing – core pre-purchase operations. Order creation is missing, but the server may be intended only for quoting.