get_manufacturerFetch a single manufacturer profile by slug. Returns the same payload that powers /[locale]/m/[slug] — base columns, the locale translation (with fallback chain), and the alternate-locale slug map.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Manufacturer slug (per-locale or base). | |
| locale | No | Locale for the returned translation. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and adds meaningful behavioral detail: the response matches the route payload, includes base columns, locale translation with fallback chain, and an alternate-locale slug map. It does not cover missing-slug behavior or default locale behavior, but it is notably 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?
One information-dense sentence with the purpose front-loaded and no filler. Every clause adds useful context about the returned payload.
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 two-parameter fetch with no output schema, the description gives a clear picture of the response composition and localization behavior. It is slightly incomplete on what happens when locale is omitted and what exactly 'base columns' are, but an agent can still invoke the 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?
Schema coverage is 100%, giving a baseline of 3. The description adds extra meaning by explaining how locale drives the translation fallback chain and that the response includes an alternate-locale slug map, going beyond the schema's one-line locale description.
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?
States a precise operation: fetch a single manufacturer profile by slug. This differentiates it from list_manufacturers, search_products, and get_product, and matches the title 'Producer profile'.
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 clearly implies when to use this tool: when you have one manufacturer slug and need a single profile. It does not explicitly name alternatives or when-not-to-use conditions, so it stops short of a 5.
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 maps to a distinct resource and action: product/manufacturer retrieval, catalog search, category listing, HS classification, dual-use screening, sanctions screening, and partnership inquiry. The compliance checks are related but clearly separated by HS-code vs. name-based screening, so an agent is unlikely to pick the wrong tool.
Most tools follow a predictable verb_noun snake_case pattern: check_, get_, list_, search_, lookup_. partnership_inquiry is the only clear deviation, using a noun phrase instead of a verb-led name, but the overall convention is still easy to infer.
Nine tools is a well-scoped size for a public B2B trade and compliance server. Each tool covers a distinct step in the catalog-discovery or pre-flight workflow, with no redundant or decorative entries.
The core workflows are covered: category browsing, product search, manufacturer retrieval, HS classification, dual-use and sanctions screening, and partnership outreach. A minor gap is the lack of direct manufacturer text/country search, which is explicitly deferred to separate Wave 3b auth tools; agents can still discover manufacturers indirectly through product search.