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1845 Smoked Meat AI Gateway

Product details

get_product
Read-onlyIdempotent

Get full detail for one product by its slug (handle): description, price, and each variant/option with price and in-stock status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesProduct slug/handle (last path segment of the product URL)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
liveNo
slugYes
imageNo
priceNo
titleYes
on_saleNo
categoryNo
in_stockNo
variantsNo
regular_priceNo

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific data fields returned, but since an output schema exists, that is not a distinct behavioral disclosure. It adds no extra context about auth, errors, or unusual behavior, so the description does not go beyond what annotations and schema already provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact sentence that front-loads the core action ('Get full detail for one product by its slug') and then lists the included fields. Every word contributes useful information, with no filler or repetition of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only single-product lookup, the description plus the fully documented schema and supporting annotations are sufficient. The output schema covers return details, annotations cover safety and repeatability, and the sole parameter is fully explained, so nothing needed for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already documents 'slug' as 'Product slug/handle (last path segment of the product URL)'. The description repeats that the product is identified by slug but adds no new meaning beyond the schema, placing it at the high-coverage baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Get'), a clear resource ('one product'), and the identifier ('slug'), then enumerates the returned data (description, price, variants/options with price and in-stock status). This clearly distinguishes get_product from siblings like list_products or search_products, which retrieve multiple products rather than one.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the usage context clear: use this tool when you need details for a single product and already know its slug. It does not explicitly name alternatives or spell out when not to use it, but the singular 'one product' plus the sibling list implies the boundary without being misleading.

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

A4/5.0
Disambiguation4/5

Most tools target distinct actions: browse, search, product detail, inventory, recommendations, cart, and store policy. The main potential confusion is between get_product and check_inventory, which both report product/variant price and stock, though list_products vs search_products is reasonably clear from descriptions.

Naming Consistency3/5

Tool names are consistently snake_case and many follow a verb_noun pattern like check_inventory, get_product, list_products, and search_products. However, best_sellers, related_products, and store_info are noun phrases, while fetch and search are bare verbs, making the naming pattern mixed but still readable.

Tool Count5/5

Eleven tools is well-scoped for an e-commerce shopping assistant covering catalog browsing, product search, inventory checks, recommendations, cart assembly, content search, and store policies. Each tool has a clear purpose and the count is neither bloated nor too thin.

Completeness5/5

The tool set covers the full shopper-facing journey: discovering categories and products, searching content, viewing product details and stock, seeing best sellers and related items, checking store policies, and building a cart. As a read-only storefront gateway, missing merchant-side operations are outside its stated purpose.

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