check_inventoryCheck current price and in-stock status for a product and each of its variants/options. Pass a product slug or search keywords. Availability is as of the latest catalog sync.
| Name | Required | Description | Default |
|---|---|---|---|
| product | Yes | Product slug, or keywords to find the product |
| Name | Required | Description | Default |
|---|---|---|---|
| live | Yes | ||
| products | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior, so the description does not need to restate those. It adds useful context beyond the annotations: availability is tied to the latest catalog sync, so results may not be real-time. It also clarifies the scope includes variants/options.
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?
Three short sentences with no filler: purpose, accepted input, and data freshness caveat. The most actionable information is front-loaded, and every sentence adds value.
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?
This is a simple one-parameter tool with a documented input schema, a present output schema, and annotations covering safety and idempotency. The description adds the important catalog-sync caveat and variant scope, so nothing essential is missing for an agent to call it correctly.
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 coverage is 100%, so the schema already documents the product parameter fully. The description restates 'product slug or search keywords' but adds little beyond the schema. This meets the baseline but does not meaningfully enhance parameter understanding.
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 uses a specific verb-check-and clearly names the resource: current price and in-stock status for a product and each variant/option. It distinguishes itself from siblings like search_products or get_product by focusing on inventory and per-variant availability.
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?
The description implies the use case: checking price and stock. However, it does not explicitly say when to prefer this tool over alternatives like get_product, search, or search_products, nor does it mention exclusions. Usage context is present but selection guidance is left to inference.
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 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.
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.
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.
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.