Low-level compatibility primitive. Resolve a Shopify Global Catalog product/variant ID or HTTPS product URL to current normalized offers. New integrations should prefer commerce_preflight.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | US | |
| identifier | Yes |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description only adds the notion of resolving to 'current normalized offers' and the low-level compatibility framing. While useful, it does not disclose return shape, failure modes, or external dependencies beyond what annotations broadly imply.
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 tight sentences with no filler. The 'low-level' positioning is front-loaded, followed by the core function and then the routing guidance. Every clause earns its place.
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?
The tool is simple, has strong annotations, and the usage guidance is good. However, with no output schema and no description of the 'country' parameter's role or accepted values, the agent lacks full information to reliably call the tool, especially for country-dependent offer normalization.
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. It does clarify the 'identifier' parameter by listing accepted forms (ID or HTTPS URL), but it says nothing about the 'country' parameter beyond schema defaults and length constraints. This is partial compensation, not full.
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?
Description states a specific verb ('Resolve') and a clear target ('Shopify Global Catalog product/variant ID or HTTPS product URL') with an explicit outcome ('current normalized offers'). It also positions itself as a 'low-level compatibility primitive', which clearly differs from the higher-level sibling commerce_preflight.
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 names the alternative: 'New integrations should prefer commerce_preflight.' This tells the agent when not to use the tool and which sibling to use instead, leaving little ambiguity about intended invocation context.
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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Most tools target distinct workflow stages (discovery, identity, claims, decision, referral), and the detailed descriptions help separate them. However, ace_check and commerce_preflight both expose ACE Verdict decisions, and verify_global_offer is an explicitly legacy alternative to commerce_preflight, so an agent can still misselect among the verification/decision tools.
All names are readable snake_case, and action tools use a verb_object pattern while query/metadata tools use noun phrases. The split is not chaotic, but it is inconsistent (e.g., product_discovery vs resolve_product_identity), and the commerce_/commercial_ prefix variation adds a minor wrinkle.
Fifteen tools is at the upper end of a well-scoped service and is reasonable for a broad commerce intelligence domain. The count feels slightly heavy because there are several descriptive/policy tools and at least one legacy overlap (verify_global_offer) that could be consolidated.
The set covers the core pre-purchase workflow: discovery, identity resolution, claim compilation, verification, recalls, merchant readiness, trust, referrals, and routing. Minor gaps exist, such as no explicit claim-management or decision-status retrieval separate from the decision products, but these do not create dead ends.