get_brandOne supplier in full: what they make, the product families they run, and — the field worth the call — doesNotDo, a statement of what they genuinely do NOT make, computed from absence in their product list rather than inferred from their marketing.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Supplier slug from list_brands. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It adds valuable nuance by explaining that doesNotDo is computed from absence in the product list rather than inferred from marketing, and it previews the response contents. It stops short of stating read-only behavior or error behavior, but no write semantics are implied.
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, front-loaded sentence that leads with 'One supplier in full' and spends zero words on filler. Every clause adds information, including the differentiating doesNotDo detail.
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-style tool with no output schema, the description provides a good preview of the response (what they make, product families, doesNotDo). It lacks explicit handling of invalid slugs or a fuller return-shape list, but nothing essential is missing for an agent deciding to call 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?
Schema coverage is 100%, so the schema already fully documents the sole slug parameter (including where to get it: list_brands). The description adds no additional parameter semantics, so it meets the baseline but does not exceed it.
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 names a specific operation and resource: retrieving one supplier profile in full, including product families and the distinctive doesNotDo field. The phrase 'one supplier in full' distinguishes it from sibling list/compare tools such as list_brands and compare_brands.
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?
No explicit when-to-use or when-not-to-use guidance is given. The wording 'One supplier in full' implies the tool is for detailed single-supplier lookups rather than enumeration, but it never names alternatives or conditions for choosing compare_brands or search_products.
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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