get_brands
List all 107 Sense2 case-study brands (Google, Nike, Mercedes, Porsche, MasterCard, etc.) with industry, headline, and URL
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List all 107 Sense2 case-study brands (Google, Nike, Mercedes, Porsche, MasterCard, etc.) with industry, headline, and URL
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It transparently states the tool returns a static list of brands with specific fields. It does not mention authentication or rate limits, but for a read-only list that is acceptable.
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?
Single sentence, front-loaded with action and examples, no unnecessary words. Highly efficient and well-structured.
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 no output schema and no parameters, the description fully covers what the tool returns: a list of brands with industry, headline, and URL, with concrete examples. Complete for the tool's simplicity.
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?
No parameters exist. The description adds meaning by detailing the content of the list (specific brands, fields) beyond what the empty schema provides. Baseline for 0 params is 4, and the description exceeds that.
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', the resource 'brands', and provides specific examples (Google, Nike) and fields returned (industry, headline, URL). It distinguishes from the singular 'get_brand' sibling.
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 implies usage for listing all case-study brands, but does not explicitly state when to use this tool versus alternatives like 'get_brand' or when not to use it. With 18 siblings, more guidance would be beneficial.
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 targets a distinct resource or action, from product and brand lookups to editorial collections and regional delivery info. Even similar listing tools (categories, industries, aesthetics, intents, inspirations, on-trend) are differentiated by their specific names and descriptions.
The naming pattern is strongly consistent: lowercase with underscores, and almost all tools use the get_ prefix plus a resource name. The only deviation is search_products, which uses 'search' instead of 'get', but it still follows the verb_noun structure.
With 21 tools, the server is on the heavy end of the typical range. The breadth is justified by the many distinct content types (products, brands, editorials, company info, reviews, regions, FAQ), but the count feels slightly bloated compared to leaner MCP servers.
The tool surface covers the full research and selection journey: product search, details, quotes, FAQ, company credibility, delivery areas, and inspirational content. The main gap is the lack of any transactional or order-placement tool, but that appears outside the intended scope.