Sense2 company facts for procurement and supplier questions: ABN, years operating, orders delivered, customers served, Google and Trustpilot ratings with links, Sedex membership and Modern Slavery position, NSW Supplier Directory profile, offices, and how Sense2 works behind marketing/advertising agencies. Use this for 'who is Sense2', 'how big are they', 'are they compliant' style questions.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It implies read-only behavior by listing facts but does not explicitly state that it is safe, non-destructive, or what the response format is. Minimal disclosure beyond the data content.
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 that is informative but somewhat lengthy due to enumeration of many data points. Front-loaded with main purpose. Could be split into two sentences for readability, but still effective.
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 parameters and no output schema, the description provides a thorough list of outputs. For a simple fact retrieval tool, this is adequately complete. Lacks only minor details like return format or limits.
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?
Input schema has zero parameters (100% coverage trivially). Description adds value by detailing the types of facts returned (e.g., Google ratings, Sedex membership), which is meaningful context beyond the empty schema.
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 uses a clear verb ('get' implied) and specifies the resource ('company facts for procurement and supplier questions') with detailed list of data points (ABN, years operating, etc.). It distinguishes itself from sibling tools that cover brands, products, and aesthetics.
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?
Explicitly states the tool is for 'who is Sense2', 'how big are they', 'are they compliant' style questions, providing clear context for use. No mention of when not to use, but sibling differentiation makes it implicit.
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.
