Retrieve a confirmed order's status, items, and payment details by order_id. customer_email is required as soft-auth and must exactly match the order record — prevents arbitrary order lookups. Returns payment status (paid | pending | failed), production status, and dispatch date once available.
| Name | Required | Description | Default |
|---|---|---|---|
| order_id | Yes | ||
| customer_email | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so thoroughly. It discloses the soft-auth requirement, exact-match rule, and the motivation (prevents arbitrary lookups). It also enumerates return fields, including the payment status enum (paid|pending|failed), production status, and conditional dispatch date, giving a clear behavioral picture.
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?
Two sentences, front-loaded with the core action, then adding essential auth and return details. Every sentence earns its place with no repetition or filler.
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 simple two-parameter getter with no output schema and no annotations, the description fully covers what the tool does, how to call it, and what it returns. It even explains the security rationale, making it independently sufficient for an agent to decide when to use it.
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 must compensate for both parameters. It does: order_id is explained as the lookup key, and customer_email is explained as soft-auth with an exact-match requirement. This adds meaningful semantic context far beyond the bare schema types.
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 begins with a specific verb-resource pair ('Retrieve a confirmed order's status, items, and payment details by order_id'), clearly distinguishing this from sibling tools that handle carts, checkouts, or product lookups. The scope is unambiguous: it targets confirmed orders, not unconfirmed checkouts or other resources.
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 clearly implies the tool is for retrieving confirmed orders and explicitly states that customer_email is required and must match exactly, which is a critical usage constraint. However, it does not mention any alternatives or explicitly say when not to use this tool versus a sibling like get_checkout, so it stops short of a 5.
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.