Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are all false/negative (readOnlyHint=false, idempotentHint=false, destructiveHint=false), so the description carries the burden of behavioral disclosure and meets it thoroughly. It discloses the side effect of creating a purchase attempt ('One approval creates one purchase attempt'), the non-idempotent retry semantics, that unknown cart outcomes 'stay on hold', and that Shopify verifies the subtotal before returning a payment link. It also enumerates the full failure surface. No contradiction with annotations.

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?

Purpose is front-loaded in the first sentence, and every sentence earns its place: prerequisites, retry semantics, quote-change handling, and failure modes. The main flaw is structural — it is one dense, unbroken paragraph with a very long error-code list appended, making it harder for an agent to scan quickly despite the high information density.

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 tool with 7 parameters, nested objects, no output schema, and sequencing dependencies on four siblings, this description is remarkably complete. It covers prerequisites, ordering, retry/quote-change behavior, the explicit return fields (quoteId, quotedSubtotal, checkoutUrl, cartId, designAssetId, lineItem) since no output schema exists, and the complete error code surface.

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% with detailed per-parameter descriptions (e.g., buyer.email 'does not prove ownership', selectedOptions keyed by option name). The description adds genuine value by linking parameters to the workflow — which prior call each token originates from (approvalId from approve_design_proof, quoteToken from get_quote, designToken from create_business_card_design) and the confirmUpdatedQuote retry semantics — context the schema alone doesn't provide.

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 opening sentence names a specific verb-resource pair ('turns a design token from create_business_card_design plus the buyer's chosen pack options and email into a Shopify checkout URL') and states the concrete output (checkout URL with print-ready artwork attached to the line item). It clearly distinguishes itself from siblings like approve_design_proof and get_quote by positioning itself as the terminal purchase step.

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?

Explicitly states when to call: 'Call this only after the buyer has approved both design previews and chosen a value for every customer-facing option get_product lists.' It enumerates required prerequisites (approvalId from approve_design_proof, quoteToken from get_quote), and gives precise when-not-to-use guidance (retries keep same approval; uncertain outcomes require recovery, never replacement; expired/changed quotes require fresh quote and renewed confirmation).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.