Convert selected product variants into an instant 1-click Shopify direct-to-checkout Cart Permalink URL with discounts.
| Name | Required | Description | Default |
|---|---|---|---|
| note | No | Optional delivery instructions to attach to the order | |
| items | Yes | Array of line items to add to the checkout cart | |
| discount_code | No | Optional promotional code to apply at checkout (e.g., 'WEBMCP10') |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does disclose the key behavior — that the result is a Cart Permalink URL rather than a placed order — but says nothing about whether the URL expires, whether the discount is validated server-side, what happens with invalid variant IDs, or whether any auth/scope is required. For a checkout-adjacent tool with zero annotation coverage, these omissions matter.
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?
A single front-loaded sentence with no wasted clauses; the resource and output are stated immediately. Minor marketing phrasing ('instant 1-click') is the only padding.
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?
With three top-level parameters, a nested items array, and no output schema, the description usefully stands in for a return-value explanation by naming the Cart Permalink URL. However, it leaves gaps around failure modes, discount validity, and how the URL should be surfaced to the user, so it is adequate rather than 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 description coverage is 100%, so every parameter and nested item field (variant_id, quantity, price, title) is already documented in the schema, which sets the baseline at 3. The description adds only that variants are 'selected' and that discount codes apply 'at checkout', which is modest added meaning.
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 gives a specific verb and output artifact: it converts selected product variants into a Shopify direct-to-checkout Cart Permalink URL, optionally with discounts. That is far more specific than the sibling tools (product search, comparison, AR, floorplan), so an agent can rule this in or out quickly. It stops short of naming a sibling to distinguish itself from, which keeps it from a 5.
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?
Usage is only implied: 'selected product variants' suggests it comes after product selection, and the mention of discounts hints at applying a promo code. There is no explicit when-to-use, no when-not-to-use, and no stated prerequisite such as looking up variant IDs via check_variant_availability first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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