Search authorized brands and manufacturers on authorized.by. Returns brand names, slugs, logos and authorized-retailer counts. Omit 'search' to retrieve the full index.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Zero-based page number (default 0). | |
| size | No | Page size (default 500). | |
| search | No | Filter by brand name or alias. Optional. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description fully discloses the return fields (brand names, slugs, logos, authorized-retailer counts) and the effect of the search parameter. It does not mention rate limits or authentication, but for a read-only list tool, the provided transparency is adequate.
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 two sentences, front-loading the purpose and adding a key usage hint. Every sentence is essential, with no redundant information.
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 tool's simplicity (3 optional parameters, no nested objects, no output schema), the description explains the core functionality and return content. It is complete enough for an AI agent to select and invoke correctly, though pagination details are more implied than explicit.
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?
With 100% schema description coverage, the baseline is 3. The description adds value by explaining that the 'search' parameter filters by brand name or alias, and that omitting it returns the full index, which is not evident from the schema alone.
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 specifies a clear action ('Search authorized brands and manufacturers') and resource ('authorized.by'), and distinguishes from siblings by mentioning it returns a list with brand names, slugs, logos, and retailer counts, contrasting with get_brand for a single brand.
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 provides explicit guidance that omitting the 'search' parameter retrieves the full index, clarifying when to use the search option. However, it does not explicitly state when to use this tool over siblings like get_brand or get_brand_retailers.
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 has a clearly distinct purpose: fetching individual brands/retailers, listing/searching them, and retrieving their cross-relationships. There is no functional overlap.
All tools follow a strict 'get_<entity>_<optional_relation>' pattern in snake_case, providing a predictable and consistent naming convention.
With 6 tools covering both entities (brands and retailers) and their bidirectional relationships, the count is well-scoped for a read-focused API.
The tool set covers all essential read operations: individual lookups, listing/search, and relationship queries for both brands and retailers, leaving no obvious gaps.
