get_product
Get full product detail by product or variant identifier.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| catalog | Yes |
Facet UCP Shopping
by llc.facet
TDQS
C2.9/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It states 'Get full product detail', implying a read-only operation. However, it does not disclose the response structure, potential limits, or whether the 'full detail' includes all fields. It is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, a single sentence that front-loads the purpose. It avoids unnecessary words, but at the cost of missing important details. It is not verbose, but the conciseness may hinder completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (nested object parameter, no output schema, no annotations), the description is incomplete. It does not explain what 'full product detail' means, how to differentiate product vs variant, or what the response contains. Sibling tools like 'lookup_catalog' are not addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It says 'by product or variant identifier' but does not explain how the single 'catalog' parameter maps to different identifiers or what 'catalog.id' represents. The description adds minimal value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get full product detail') and the method ('by product or variant identifier'). It distinguishes from sibling tools like 'search_catalog' which are broader. However, the input schema uses 'catalog.id' which could be ambiguous, but the description compensates by mentioning both product and variant identifiers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'lookup_catalog' or 'search_catalog'. It does not specify prerequisites or scenarios where this tool is appropriate.
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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TDQS
A3.6/5.0
Disambiguation3/5
Most tools map to a distinct lifecycle step, and the detailed descriptions separate discovery, cart, checkout, payment, order, and wishlist concerns well. However, get_product and lookup_catalog are largely the same lookup by identifier, discover_products and search_catalog overlap across scope, and update_checkout is actually a read-only no-op.
Naming Consistency4/5
The set overwhelmingly follows a verb_noun pattern: create_cart, get_checkout, cancel_checkout, complete_checkout, search_catalog. Minor deviations are the wishlist_* resource-first subgroup and the misleading update_checkout, which does not perform an update.
Tool Count3/5
At 23 tools, this sits at the heavy end of the range, though the broad commerce lifecycle does justify substantial surface area. The count is inflated by redundant product lookup tools and a no-op update_checkout, so a more trimmed set in the low-to-mid teens would be healthier.
Completeness4/5
The server covers the full shopper lifecycle well: discovery, product lookup, cart, checkout, payment, order placement, order read, refunds, and wishlist. Gaps are minor and workable, such as update_checkout not actually supporting updates and no explicit order-cancellation path once a checkout is complete.