Return complete detail for one product, identified by its slug: description, wholesale price, category, brand, care instructions, occasion tags and a virtual-proof link. Use after search_products when one item needs full detail before quoting it.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug (from search results) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of disclosing behavioral traits. It mentions returning data but does not explicitly state that the operation is read-only, nor does it address authentication requirements, rate limits, or error behavior. The implicit 'Return' suggests a read operation, but this is not made explicit.
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, well-structured sentence that packs the function, the input, and the output fields without fluff. It also includes the usage guidance in the same breath, making it compact yet highly informative.
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 simple single-parameter tool, the description provides sufficient context: it names the output fields, explains the input source, and gives a usage scenario. It does not describe return format or error cases, but these are not essential for a straightforward get operation. The description is complete enough for an agent to decide when and how to invoke it.
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 only parameter, 'slug', is fully described in the schema as 'Product slug (from search results)', and the main description reiterates that the tool identifies the product by its slug. The schema coverage is 100% and the description adds the source context (from search results), meeting the baseline for full parameter meaning.
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 a specific verb ('Return'), a resource ('complete detail for one product'), and identifies the input (slug). It also lists the exact fields returned, making the tool's purpose unmistakable and distinguishing it from sibling tools like search_products or get_product_catalog.
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 explicitly states when to use this tool: 'Use after search_products when one item needs full detail before quoting it.' This provides a clear trigger and context, though it only names one sibling (search_products) rather than all alternatives, leaving some implicit exclusion of other tools like get_product_catalog.
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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