Menlo Labs Shopping MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must convey all behavioral traits. It only describes the output (curated shopping list) without disclosing side effects, safety (e.g., mutability), authentication needs, or constraints like rate limits or data sources. This is a significant gap.

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 extremely concise: two sentences totaling 18 words. It front-loads the core purpose and immediately follows with usage examples. Every word serves a purpose, with no fluff or redundancy.

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's complexity (5 parameters, no output schema, no annotations), the description is insufficient. It lacks essential context about return format, error handling, parameter dependencies, and output structure. The agent has little guidance beyond the basic purpose.

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%, meaning the schema provides no parameter explanations. The description only mentions 'goal or theme', which loosely maps to the 'theme' parameter, but it ignores 'sort', 'budget', 'max_categories', and 'products_per_category'. No meaningful semantic addition over the 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 clearly states the tool's action ('Build a curated shopping list') and resource ('for a goal or theme'). It provides specific use cases (setups, gift lists, starter kits, multi-category recommendations) that distinguish it from the sibling tool 'search_products', which likely retrieves individual products without curation.

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 includes explicit use cases (setups, gift lists, starter kits) but does not state when not to use this tool or provide direct comparison to the sibling 'search_products'. The guidance is implied but not sufficiently explicit for full usage clarity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It mentions price and rating filters but omits crucial details like pagination (max_results), domain selection, sponsored exclusion, and what happens on no results or errors. The behavioral disclosure is minimal.

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 a single concise sentence that front-loads the core purpose. Every word adds value without unnecessary elaboration.

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?

With 8 parameters, no output schema, and no annotations, the description needs to be comprehensive. It covers only query and filters, missing most parameter contexts and any return value or behavior details. This is inadequate for a tool of this complexity.

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 description only covers 'price and rating filters', but there are 8 parameters in the schema with zero schema descriptions. It does not explain 'sort', 'max_results', 'amazon_domain', 'exclude_sponsored', or 'query' beyond the general mention. This leaves agents guessing about most parameters.

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 finds individual products matching a query, which is the primary purpose. It mentions support for filters, but does not explicitly differentiate from the sibling tool 'build_product_kit', though the purpose is distinct enough.

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', providing basic context. However, it does not specify when not to use it or mention alternatives, such as when to prefer the sibling tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.