Put these items in the shop's cart and hand back the link that opens checkout. Nothing is charged and no account is needed — the customer pays as a guest, exactly as on the website. Use this for an ordinary purchase.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide readOnlyHint/idempotentHint/destructiveHint, and the description adds useful behavioral context: nothing is charged, no account is needed, and the customer pays as a guest. This meaningfully clarifies the tool's side-effect profile beyond the annotations, though it does not discuss things like link expiry or checkout session limits.
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 three well-organized sentences: action and output, cost/account behavior, and usage guidance. Every sentence contributes useful information and there is no unnecessary repetition of the tool name or schema details.
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 this is a one-parameter tool with no output schema, the description is largely complete: it covers what happens, what the tool returns, the guest-payment behavior, and the intended use case. The main missing piece is parameter semantics around the item slug, but overall the definition is adequate for inspection and safe 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?
Schema description coverage is 0%, so the description needed to compensate, but it only says 'these items' without explaining what `slug` means, where valid slugs come from, whether quantity is required, or how the items array should be formed. The schema shows the shape, but the description adds very little parameter-level meaning beyond the property name.
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 states a specific action and output: 'Put these items in the shop's cart and hand back the link that opens checkout.' This clearly distinguishes start_checkout from the sibling tools, which are mostly read/search/payment-link tools, and makes the ordinary-purchase checkout purpose explicit.
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 a clear usage context: 'Use this for an ordinary purchase' and clarifies that it does not charge or require an account. It does not explicitly name sibling alternatives like create_payment_link or state when not to use it, so it stops short of full exclusion guidance.
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.
Each tool has a clearly distinct purpose: checkout flows are separated into start_checkout (guest) and create_payment_link (token-based), product discovery has list/search/get, and order tracking, reviews, shop info, and analytics are each unique. No two tools could be easily confused.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_payment_link, list_products, get_order_status), with only shop_info and usage_report as minor noun-style exceptions but still clear and predictable. The naming style is uniform.
With 9 tools, the server is well-scoped for an e-commerce assistant. Each tool covers a distinct operation—browsing, searching, ordering, checkout, reviews, shop info, and analytics—without redundancy or bloat.
The tool set covers the full lifecycle for a shop assistant: product discovery, details, reviews, checkout initiation, order status, and even administrative usage reporting. No critical gaps exist—no required operations like updating orders or managing carts are missing for the intended use case.