get_intents
List all 30 Shop by Intent curated collections (VIP client gifts, conference swag, onboarding kits, etc.) with product counts and URLs
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Sense2 Promotional Products
TDQS
A3.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals output includes product counts and URLs, but lacks details like fixed 30 count, ordering, or read-only nature. Missing behavioral traits beyond basic listing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with clear verb-first structure. Every word is informative with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters or output schema, the description adequately covers purpose and output. Minor gap: doesn't confirm if list is always 30 or if pagination applies, but minimal impact for such simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, schema coverage 100%. Description adds value by confirming 'all 30' and specifying output fields, which is sufficient baseline for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 30 Shop by Intent curated collections', with specific examples of collections and output fields. It distinguishes itself from siblings like 'get_categories' which have different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., 'get_buyer_missions', 'get_categories'). No mention of when not to use or prerequisite context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A3.6/5.0
Disambiguation5/5
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.
Naming Consistency4/5
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.
Tool Count3/5
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.
Completeness4/5
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.