Search authorized retailers (shops) on authorized.by. Returns retailer names, slugs, shop URLs, logos, authorized-brand counts and seal_implemented (whether the authorized.by seal is live on their shop). 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 retailer company name or alias. Optional. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It discloses return fields and the platform. It does not mention pagination behavior, rate limits, authentication, or that it is a read-only operation. While it provides useful output context, it lacks some behavioral details that would help an agent plan calls.
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, no filler. The first cover purpose and outputs, the second gives a concise usage instruction. Every part adds value.
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 three well-documented parameters, no output schema, and sibling tools, the description sufficiently covers core functionality and key usage. It lacks details on result ordering, error handling, or limits, but remains adequate for typical agent usage.
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% with individual parameter descriptions. The description adds value by explaining that omitting 'search' retrieves the full index, which clarifies the parameter's role. It also lists returned fields, indirectly helping understand parameter effects.
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 explicitly states the verb 'Search' and the resource 'authorized retailers (shops) on authorized.by'. It lists specific return fields (names, slugs, URLs, logos, counts, seal_implemented) and contrasts with the full index variant. This clearly distinguishes it from sibling tools like get_retailer (singular) and get_brand_retailers.
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 notes when to use it ('search' filter) and provides the tip to omit 'search' for the full index. However, it does not explicitly recommend against using it when a single retailer is needed (suggest get_retailer) or mention when other sibling tools are more appropriate.
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.
