Verify whether a specific colour is available before configure_product. Returns in_stock boolean, expected_restock_date if out of stock, and up to 5 alternative in-stock colours ordered by similarity. Call this when a customer requests a named colour or when you want to prevent a configure_product failure due to an out-of-stock selection.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | ||
| colour_name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return shape (in_stock boolean, expected_restock_date, up to 5 alternatives) and frames the tool as a read-only verification via 'Verify' and 'Returns'. It stops short of error handling details, but the safety profile is evident.
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: the first states purpose, the second covers output and usage triggers. Every word earns its place, and the description is well 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?
For a two-parameter read-only tool with no output schema, the description covers return values, usage context, and practical reason for existing. It lacks error behavior, but given the small scope, it is nearly complete.
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 coverage is 0%, so the description must compensate. It indirectly references both parameters ('specific colour' for colour_name, and the configure_product context implies product_id), but does not explicitly map them or provide format constraints. Given the simplicity of the two parameters, the minimal compensation is adequate but not thorough.
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 a specific action, 'Verify whether a specific colour is available', and clearly identifies the resource (colour) and its role as a pre-check for configure_product. This distinguishes it from siblings like search_catalog or get_product.
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?
Provides explicit when-to-use guidance: 'Call this when a customer requests a named colour or when you want to prevent a configure_product failure due to an out-of-stock selection.' It lacks explicit alternatives, but the context is strong enough to guide the agent.
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.