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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions what information is returned (addresses, phone numbers, store hours), it doesn't describe important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or how results are structured/limited. The description provides basic output content but lacks operational context.

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, efficient sentence that front-loads the core purpose and includes all essential information without unnecessary words. Every element (what it finds, search criteria, returned data) earns its place with zero waste.

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 lookup tool with 2 parameters and 100% schema coverage, the description provides adequate basic context about what the tool does and what information it returns. However, with no annotations and no output schema, it should ideally provide more behavioral context about how results are returned (format, limitations, pagination) and operational considerations.

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 100%, so the schema already documents both parameters (zip and radius) with their types and descriptions. The description adds marginal value by implying the ZIP code is for proximity searching and mentioning the radius concept ('near a ZIP code'), but doesn't provide additional syntax, format details, or constraints beyond what the schema provides.

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 specific action ('Find Trader Joe's store locations'), the resource ('store locations'), and distinguishes from siblings by focusing on physical stores rather than products. It specifies what information is included (addresses, phone numbers, store hours) and the search context (near a ZIP code).

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?

No guidance is provided on when to use this tool versus the sibling tools (get_new_products, get_product_details, search_products). The description implies usage for finding physical store information, but doesn't explicitly contrast with product-focused alternatives or mention any prerequisites or exclusions.

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?

With no annotations, the description carries full burden but only states what the tool does, not behavioral traits like rate limits, authentication needs, or response format. It lacks details on whether this is a read-only operation or has other constraints.

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, efficient sentence that front-loads the core purpose without unnecessary words. Every part earns its place, making it highly concise and well-structured.

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 read tool with one optional parameter and no output schema, the description is adequate but incomplete. It lacks behavioral context and usage guidance, which are needed given the absence of annotations and output schema.

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 100%, so the schema fully documents the optional 'category' parameter. The description doesn't add meaning beyond this, such as explaining category examples or filtering logic, meeting the baseline for high coverage.

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 action ('Get a list') and resource ('new and featured products at Trader Joe's'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'search_products' or 'get_product_details', which prevents a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives like 'search_products' or 'get_product_details'. The description implies it's for new/featured items, but it doesn't specify exclusions or contexts, leaving usage unclear.

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 carries full burden. It states it's a read operation ('Get'), which is clear, but doesn't disclose behavioral traits like error handling (e.g., what happens if SKU is invalid), rate limits, authentication needs, or response format. For a tool with no annotations, this leaves significant gaps.

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, well-structured sentence that efficiently conveys the tool's purpose and key details without any wasted words. It's appropriately sized and front-loaded with essential information.

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 low complexity (1 parameter, no nested objects) and high schema coverage, the description is adequate but incomplete. With no annotations and no output schema, it should ideally provide more behavioral context (e.g., response format, error cases) to fully compensate, leaving some gaps.

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 100%, with the schema documenting the 'sku' parameter as 'Product SKU from search results'. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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 verb 'Get' and resource 'detailed information about a specific Trader Joe's product by SKU', with specific content details like 'ingredients, nutrition facts, and allergens'. It distinguishes from sibling tools like 'search_products' (which likely returns multiple results) by focusing on a single product lookup.

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 usage when you need detailed info for a specific product identified by SKU, but doesn't explicitly state when to use this vs. alternatives like 'search_products' or 'get_new_products'. No guidance on prerequisites or exclusions is provided.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return data (product names, SKUs, prices, descriptions) but omits critical details like whether this is a read-only operation, potential rate limits, authentication needs, or pagination behavior. For a search tool with zero annotation coverage, this is a significant gap in 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 appropriately sized with two concise sentences that front-load the core functionality. Every sentence earns its place by stating the action and return values, though it could be slightly more structured (e.g., separating usage from output). No wasted words, but minor room for improvement in flow.

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 moderate complexity (search with two parameters), 100% schema coverage, and no output schema, the description is minimally adequate. It covers the basic purpose and return data but lacks behavioral context (e.g., error handling, limitations) and usage guidelines, making it incomplete for optimal agent operation without additional inference.

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 100%, so the schema already documents both parameters ('query' and 'page_size') thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as search syntax examples or result ordering. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb ('Search for') and resource ('products at Trader Joe's'), specifying what the tool does. It distinguishes from siblings like 'find_stores' (location search) and 'get_product_details' (specific product lookup), though not explicitly. However, it doesn't fully differentiate from 'get_new_products' (which might also return product info), keeping it from a perfect score.

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 provides no guidance on when to use this tool versus alternatives like 'get_new_products' or 'get_product_details'. It implies usage for keyword-based searches but lacks explicit when/when-not instructions or prerequisites, leaving the agent to infer context without clear direction.

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