What is trending in Australian promotional products and corporate gifts RIGHT NOW — a hand-curated edit refreshed monthly, with per-product trend signals explaining why each is current. Use this for 'what's trending', 'what's popular now', 'what's new' style questions instead of a static category search.
| 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. Discloses hand-curated nature, monthly refresh, and per-product trend signals. No behavioral contradictions.
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. Front-loaded with key information (trending products, location, refresh cycle). Every sentence 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?
Given zero parameters and no output schema, description sufficiently explains what is returned and when to use. Could specify if output is a list or single item, but still clear.
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; schema coverage 100%. Description adds value by explaining output content and update frequency, meeting baseline for zero-param tools.
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?
Description specifies it returns trending Australian promotional products/corporate gifts, hand-curated and refreshed monthly with trend signals. Clearly distinguishes from static category search.
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 when to use ('what's trending', 'what's popular now', 'what's new' style questions) and contrasts with static category search. Lacks explicit when-not-to-use but adequate.
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.
