Search Amazon products by price and rating, or build curated shopping kits for any goal.
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Average 3.5/5 across 2 of 2 tools scored.
build_product_kit is for creating curated multi-item lists, while search_products finds individual products. Their purposes are clearly different, and the descriptions reinforce the distinction, leaving no ambiguity.
Both tools use a consistent verb_noun pattern with snake_case, making the set predictable and easy to navigate. The naming style is uniform and intuitive.
With only two tools, the server feels thin for a shopping domain, but the pair covers both product search and curated list building, which are core use cases. This is borderline but not excessive.
The set covers product search and curated list creation, but lacks explicit product detail retrieval or list management. However, search likely returns sufficient details, and kits are generated on demand, so the gaps are minor.
build_product_kitBInspectBuild a curated shopping list for a goal or theme. Use for setups, gift lists, starter kits, or multi-category recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | best_match | |
| theme | Yes | ||
| budget | No | ||
| max_categories | No | ||
| products_per_category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It states the high-level action (building a curated list) but does not explain how the curation works, whether it involves side effects, what output format to expect, or any constraints. The description is too thin to inform the agent about important behavioral traits.
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?
The description is two short sentences, front-loaded with the main action and followed by usage examples. Every word contributes to understanding, and there is no redundancy. This is appropriately concise.
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?
The tool has five parameters, no output schema, and no annotations. The description provides only a high-level purpose and usage context but does not explain return values, parameter effects, or edge cases. The complexity of the tool warrants more detail than this description offers, making it incomplete.
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?
The schema description coverage is 0%, and the description provides no meaning for any of the five parameters (theme, sort, budget, max_categories, products_per_category). The parameter names are somewhat self-explanatory, but the description adds zero value over the schema, failing to explain how they interact or affect the result. This is a critical gap.
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 tool's function: 'Build a curated shopping list for a goal or theme.' It specifies the resource (shopping list) and the verb (build), and distinguishes itself from the sibling search_products by focusing on multi-category curated outputs. The use cases (setups, gift lists, starter kits) further clarify purpose.
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 explicitly lists when to use the tool: 'Use for setups, gift lists, starter kits, or multi-category recommendations.' However, it does not name the sibling tool as an alternative or state when not to use it, so it falls short of a 5. The context is clear but lacks explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsAInspectFind individual products matching a query. Use for a specific item or category; supports price and rating filters.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | best_match | |
| query | Yes | ||
| max_price | No | ||
| min_price | No | ||
| min_rating | No | ||
| max_results | No | ||
| amazon_domain | No | amazon.com | |
| exclude_sponsored | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool supports price and rating filters, but omits other behavioral traits such as the default sorting, sponsored filtering, or the Amazon domain parameter. The term 'Find' implies a read-only operation, but more detail on response behavior would improve transparency.
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?
The description is two sentences long, front-loaded with the primary purpose, and contains no fluff. Every phrase earns its place, including the filter capabilities note.
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 the tool has 8 parameters, no output schema, and no annotations, the description is too sparse. It does not explain return structure, pagination, or how filters interact, leaving substantial gaps for an agent to use the tool correctly.
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 description coverage is 0%, so the description must compensate. It mentions price and rating filters, which roughly maps to min_price, max_price, and min_rating, but does not explain the purpose of sort, exclude_sponsored, amazon_domain, max_results, or query semantics. For 8 parameters, this is insufficient compensation.
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 tool's function with a specific verb ('Find individual products') and a resource ('matching a query'). It also distinguishes from the sibling tool by emphasizing 'individual products' versus 'build_product_kit', making the boundary explicit.
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 advises using it for 'a specific item or category', which provides clear context for appropriate use. It implicitly contrasts with the sibling tool 'build_product_kit' but does not explicitly mention when not to use it or alternative tools.
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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{
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