Products gaining momentum — most-added to wishlists in the last 30 days (aggregate counts only).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| products | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. Description adds that results are aggregate counts only and limited to the last 30 days, which is useful behavioral context beyond the annotations.
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?
One sentence, front-loaded with key information, every word adds value. Efficient and clear.
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 tool with one optional parameter, an output schema, and comprehensive annotations, the description adds the missing time-window and aggregation context. No further information is needed.
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?
Schema coverage is 0% (no descriptions for parameters). The single 'limit' parameter is not mentioned in the description; no additional meaning is provided beyond the schema type and constraints.
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 clearly states the tool retrieves products gaining momentum based on wishlist additions in the last 30 days. It distinguishes from sibling 'get_popular_products' by specifying the metric (wishlist adds) and time window.
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 use when trending products by wishlist counts are needed, but does not explicitly state when not to use or mention alternatives. The clear context is sufficient for general guidance.
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 are distinct, but 'fetch' and 'get_product' have overlapping functionality (both provide full detail and buying options), and 'search' vs 'search_catalog' could confuse agents about which to use for general search. Otherwise clear.
Predominantly uses 'get_' prefix for retrieval tools and 'search' for search tools, but 'fetch' and 'lookup_catalog' deviate slightly from the pattern, reducing consistency.
13 tools is well-scoped for a commerce server covering product discovery, pricing, deals, collections, and gift ideas without being overwhelming or sparse.
Covers key product research and price comparison workflows, but lacks tools for user interaction (e.g., wishlists, purchasing) or multi-product comparisons, which would enhance completeness.
