[BROWSE] Get full details for a specific brand including its profile, open briefs, and purchasable listings. Provide a brand_slug from list_brands.
| Name | Required | Description | Default |
|---|---|---|---|
| brand_slug | Yes | Brand slug (e.g. "rrg", "my-brand") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the scope of data returned (profile, open briefs, purchasable listings) and the [BROWSE] prefix suggests a non-mutating read operation. While it doesn't mention auth requirements or error handling, for a simple get tool, the 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 a single, compact sentence plus a short imperative instruction. It is front-loaded with the core purpose, includes no fluff or repetition, and every word earns its place.
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?
The tool has only one parameter and no output schema, but the description covers the essential context: what the tool does, what data it returns, and where to get the input. It does not describe return structure or error cases, but for a narrowly-scoped get tool with good sibling context, it is sufficiently 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 100% (brand_slug is described with an example), so the baseline is 3. The description adds value by explaining how to obtain the parameter value: 'Provide a brand_slug from list_brands.' This contextual instruction goes beyond the schema's static description and helps the agent execute the correct workflow.
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's function: 'Get full details for a specific brand including its profile, open briefs, and purchasable listings.' It uses a specific verb ('Get') and resource ('brand details'), and distinguishes itself from sibling tools like list_brands by focusing on a single brand rather than listing all 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?
The description explicitly tells the agent how to use the tool: 'Provide a brand_slug from list_brands.' This gives clear context on the prerequisite step and the source of the parameter value. It doesn't mention when not to use it or alternatives, but the guidance is sufficient for a single-purpose tool.
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.
Most tools have distinct purposes with clear category tags. Minor potential confusion between get_current_brief vs list_briefs and get_brand vs get_brand_mcp_endpoint, but descriptions clarify intent.
All tools follow a consistent verb_noun pattern using lowercase with underscores, e.g., check_agent_standing, list_drops, submit_design. No mixing of conventions.
32 tools is on the high side, but the server covers a wide domain including browsing, purchasing, design submission, concierge, and marketing. Each tool serves a specific function, though some consolidation could be possible.
The tool surface covers the full lifecycle of browsing, purchasing, design creation, commissions, and concierge services. Minor gaps like refund handling are absent, but the core workflows are well-supported.