get_productGet public catalog details for a Renew product: description, use/appliance compatibility, public feature highlights, packaging/availability, regulatory status, manufacturer, country of origin and canonical URL. Returns no ingredient, formula or chemical data (none exists in the catalog).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| locale | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only. The description adds value by explicitly listing returned fields and stating what is excluded (no ingredient data), providing clear behavioral context beyond annotations.
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 wasted words. The first sentence front-loads what the tool returns, and the second clarifies an important exclusion.
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 read operation with enums and no output schema, the description adequately specifies return fields and exclusions. It is missing optionality info for locale but is otherwise complete.
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 0%, meaning no parameter descriptions in schema. The description does not explain the 'slug' or 'locale' parameters; the enum values are the only clues. This is insufficient for a 2-parameter tool.
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 the tool retrieves public catalog details for a Renew product, listing specific fields. It distinguishes from siblings like list_products by focusing on a single product identified by slug.
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 use when needing product details but does not explicitly contrast with siblings or state when not to use. No alternative recommendations are provided.
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 targets a distinct aspect: company info, distribution info, product details, and product listing. No overlapping purposes, so an agent can clearly differentiate them.
All tool names follow the verb_noun pattern using snake_case (get_company_info, get_distribution_info, get_product, list_products). Consistent and predictable naming.
Four tools is appropriate for a focused server providing public information about a dental supply company and its products. The count is slightly low but well-scoped for the purpose.
The tool set covers the core public-facing aspects: company info, distribution, product listing and details. Missing search or filtering capabilities, but for a simple catalog, it's reasonably complete.