get_productFetch current price, stock and details for one Gameshop Enter product by its SKU (as returned by search_products). Includes the direct product-page URL to buy it.
| Name | Required | Description | Default |
|---|---|---|---|
| sku | Yes | Product SKU, e.g. "GBA-177714825902" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It communicates that this is a non-mutating fetch that returns current price, stock, and product details, and it adds the useful detail that the SKU must come from search_products. It does not cover error behavior or exact response structure, but for a simple read operation it is reasonably transparent.
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 sentences with no filler. The most important information—what fields are fetched and how to obtain the SKU—is front-loaded, and the sibling reference is woven in without extra verbosity.
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 one-parameter, read-only lookup tool, the description covers the input source, the output content, and the product-page URL. There is no output schema, but the listed return fields are sufficient for an agent to know what to expect. Minor gaps like error behavior are not material to invoking this tool 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?
The schema already documents the single 'sku' parameter with 100% coverage and an example. The description adds meaningful provenance by stating the SKU is 'as returned by search_products', which helps the agent know how to obtain a valid value, going beyond the bare schema.
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 states a clear verb ('Fetch'), a specific resource ('one Gameshop Enter product'), and the key identifier ('by its SKU'). It also differentiates itself from search_products by explicitly sourcing the SKU from that sibling tool, so an agent can tell the two apart.
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 gives clear context: use this tool when you already have a product SKU, and obtain that SKU via search_products. It does not explicitly enumerate alternatives or exclusions beyond search_products, but the usage context is unambiguous enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct function: product lookup, quote calculation, catalog search, and store information. There is no overlap in their purposes, so an agent can easily select the right tool for a given task.
All tool names follow a consistent verb_noun pattern: get_product, get_quote, search_products, store_info. The prefixes 'get_', 'search_', and 'store_' clearly indicate the action and resource, making the set predictable.
With only 4 tools, the server is tightly scoped to a storefront workflow: search, product details, pricing with shipping, and store policies. Each tool is necessary and the count feels right for the domain.
The set covers the essential customer journey: searching, viewing products, obtaining a quote with checkout URL, and accessing store info. A minor gap is the lack of direct order placement or cart tools, but those appear to be handled externally via the checkoutUrl, so the surface is reasonably complete.