[BROWSE] List all active brands on the platform. Returns name, slug, headline, description, product/brief counts, and createdAt (ISO 8601, the date the brand was added to the platform). Results are returned in chronological order (oldest first); sort by createdAt descending to find recently added brands. Use a brand slug with list_drops or list_briefs to filter by brand.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals that results are in chronological order, lists the exact fields returned, and specifies the ISO 8601 format of createdAt. It does not mention pagination, rate limits, or authentication requirements, but for a simple read-only list, this is adequate. The '[BROWSE]' tag further signals a safe, non-mutating operation.
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 compact three-sentence paragraph that front-loads the purpose with '[BROWSE]'. Each sentence earns its place: purpose and scope, return fields and date format, and sorting/usage guidance. There is zero fluff or repetition.
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 list tool with no output schema, the description explains the return fields and ordering, which is essential. It also connects to sibling tools for filtering. It does not mention pagination or result limits, which could be relevant, but for a browse-all operation the given context is largely 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?
The tool has zero parameters, and the schema covers 100% of them (vacuously). The description does not need to explain parameter meanings because there are none. The baseline for 0 params is 4, and the description adds no conflicting or redundant parameter information.
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 verb 'List' and the resource 'all active brands' on the platform. It distinguishes itself from siblings like get_brand (single brand) and list_drops/list_briefs (different resources) by explicitly mentioning how to use a brand slug with the latter tools. The scope is precise: 'active 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 provides clear context for browsing all brands and notes that sorting by createdAt descending reveals recently added brands. It also tells the user to use list_drops or list_briefs with a brand slug to filter by brand, which is an alternative usage. However, it does not explicitly state when to use get_brand or register_brand, though the browsing intent is clear.
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.