Poll a checkout by checkout_id. Returns status (pending | paid | cancelled), full item list, customer details, and payment_url if already minted. Use to verify customer details before calling complete_checkout, or to retrieve the payment_url if complete_checkout was already called.
| Name | Required | Description | Default |
|---|---|---|---|
| checkout_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosure. It clearly states what the tool returns, including the conditional payment_url ('if already minted'), and the verb 'poll' implies a non-destructive read operation. It does not mention error handling or rate limits, but for a simple retrieval tool, this is reasonable and non-contradictory.
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 long, front-loaded with the core action, and every clause serves a distinct purpose. There is no filler or redundancy.
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 single-parameter tool with no output schema, the description covers the key aspects: what it does, what it returns, and when to use it. It omits potential failure modes or detailed return structure, but the listed return items give sufficient context for an agent to choose 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?
The schema description coverage is 0%, so the description must compensate. It mentions checkout_id as the tool's input and clarifies its role as the identifier used to poll a checkout. While this adds some semantic context, it provides no format examples or constraints beyond what the schema's type 'string' already implies. The description adds a bit of meaning but not enough to fully compensate for the lack of schema documentation.
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 'Poll a checkout by checkout_id,' which pairs a specific verb ('poll') with a clear resource ('checkout'). It further distinguishes itself by itemizing the returned data (status, item list, customer details, payment_url), setting it apart from sibling tools like get_cart or get_order.
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?
Explicit usage guidance is provided: 'Use to verify customer details before calling complete_checkout, or to retrieve the payment_url if complete_checkout was already called.' This tells the agent precisely when to invoke this tool and references a sibling tool to clarify the workflow.
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.
Most tools have clearly distinct purposes, but search_products and lookup_catalog overlap significantly in filtering by category and dimensions, which could confuse an agent. The three search/filter tools have subtle differences described, but the overlap lowers the score from perfect.
All tools use consistent snake_case with verb-noun structure (e.g., cancel_cart, get_product, update_checkout). There is no mixing of conventions, and the verbs clearly indicate the action, making the set predictable and easy to parse.
26 tools is slightly above the typical well-scoped range of 3-15, but the domain of an e-commerce blinds shop with additional services like AR, swatches, and price matches justifies the count. A couple of legacy tools (create_order, submit_enquiry) add minor bloat.
The core purchase flow (search, configure, cart, checkout, payment, order tracking) is fully covered. Additional services like AR visualization, swatches, price match, and WhatsApp handoff are present. Missing features like order listing or coupon application are minor gaps.