get_productFull details for one product: description, price (EUR, incl. VAT), EAN, live stock, categories, page URL and all image URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language for names and descriptions (default en) | |
| bam_id | Yes | Product id from search or listing results |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is transparent about what the tool returns, listing all data fields. Since it is a 'get' operation, it is implicitly read-only, but this is not explicitly stated. The absence of annotations means the description carries the burden, but the verb 'get' and the listing of details make the behavior clear enough.
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?
The description is a single, concise sentence that effectively communicates the scope and contents of the response. It uses a clear structure, listing the included attributes without unnecessary detail, making it easy to parse.
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?
Given the simplicity of the tool (two parameters, no output schema), the description is sufficiently complete: it covers what the tool returns and the purpose of each parameter. It does not mention error handling or edge cases, but these are not critical for a simple get operation. The absence of output schema means the description must imply the return format, which it does through the list of fields.
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?
Both parameters have descriptions: lang explains the language and default value ('default en'), and bam_id specifies it is the product id from search or listing results. These add semantic value beyond the schema, clarifying the meaning and origin of the inputs, exceeding the baseline for full coverage.
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 clearly states that the tool returns 'full details for one product', specifying the exact items included (description, price, EAN, stock, categories, URLs). The title 'Get product details' reinforces the action. It is distinct from sibling tools that list or search products, focusing on a single product's complete information.
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 that this tool is for retrieving a single product's full details, but it does not explicitly state when to use it over alternatives like search_products or list_products. It lacks explicit guidance on use cases (e.g., 'Use this when you have a specific product ID and need comprehensive information').
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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Each tool has a clearly distinct purpose: browse_catalog returns the navigation tree, list_products returns products with optional facet filtering, get_product returns full details for a single product, and search_products performs keyword search. There is no meaningful overlap between them.
All tool names follow a consistent snake_case verb_noun pattern: browse_catalog, get_product, list_products, search_products. This makes the API predictable and easy to navigate.
Four tools is a well-scoped size for a read-only catalog server. Each tool serves a distinct and necessary part of the browsing workflow, and no tool feels redundant or missing.
The tool surface covers the core catalog operations: exploring structure, filtering by facet, retrieving details, and searching. There are no obvious dead ends for typical catalog queries, and the read-only scope does not require update or delete operations.