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 states the tool adds to a cart but doesn't mention whether this requires user authentication, what happens on success/failure, if there are rate limits, or if the cart persists across sessions. This leaves significant gaps for a mutation tool.

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 briefly mentions optional parameters. There is zero wasted text, making it appropriately sized for its purpose.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error handling, authentication needs, or how it interacts with sibling tools. Given the complexity of e-commerce operations, more context 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?

The schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value by mentioning optional quantity and variant, but doesn't provide additional syntax, format details, or examples beyond what's in 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 action ('Add a product') and resource ('to the PetSmart shopping cart'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'checkout' or 'get_product_details', which would require a 5.

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 'checkout' or 'search_products'. It mentions optional parameters but doesn't specify prerequisites, error conditions, or appropriate contexts for invocation.

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 full burden for behavioral disclosure. It mentions 'initiate checkout' but doesn't clarify whether this actually completes the purchase, requires payment, triggers shipping, or has side effects like emptying the cart. For a mutation tool with zero annotation coverage, this leaves critical behavioral aspects unspecified.

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?

Two concise sentences that efficiently state the tool's purpose. The first sentence covers the main action, and the second clarifies the shipping focus. No wasted words, though it could be slightly more front-loaded with behavioral context.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after checkout initiation (e.g., order confirmation, errors, cart status), behavioral implications, or success criteria. Given the complexity of a purchase process, this leaves significant gaps for an AI agent.

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 all parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'shipping information' and 'initiate checkout,' but doesn't provide additional context about parameter usage, constraints, or relationships beyond what's in the schema descriptions.

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 purpose: 'Complete the purchase process for items in the PetSmart shopping cart. Fills in shipping information to initiate checkout.' It specifies the verb ('complete'), resource ('purchase process'), and scope ('PetSmart shopping cart'), but doesn't explicitly differentiate from siblings like 'add_to_cart' beyond the checkout vs. cart addition distinction.

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 explicit guidance on when to use this tool versus alternatives. The description implies it's for finalizing purchases after items are in the cart, but doesn't mention prerequisites (e.g., items must be in cart first), exclusions, or comparisons with other tools like 'add_to_cart' or 'find_store' for pickup options.

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 the full burden of behavioral disclosure. It mentions the tool finds store information but does not describe behavioral traits like whether it requires authentication, rate limits, error handling, or the format of returned data. This is a significant gap for a tool with no 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?

The description is a single, efficient sentence that front-loads the core purpose ('Find nearby PetSmart store locations') and adds useful details ('with information about available services, hours, and contact details') without any wasted words. It is appropriately sized for the tool's complexity.

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 lack of annotations and output schema, the description is incomplete. It does not explain what the return values look like (e.g., list format, error cases) or address behavioral aspects like permissions or limitations, which are crucial for a tool with 5 parameters and no structured output documentation.

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 all parameters thoroughly. The description adds minimal value beyond the schema by implying filtering by services and location, but does not provide additional syntax or format details. This meets the baseline for high schema 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 tool's purpose: 'Find nearby PetSmart store locations' with specific information about 'available services, hours, and contact details.' It uses a specific verb ('Find') and resource ('PetSmart store locations'), but does not explicitly distinguish it from sibling tools like 'schedule_grooming' or 'schedule_training,' which are related but different actions.

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. It does not mention prerequisites, exclusions, or compare it to sibling tools such as 'search_products' or 'add_to_cart,' leaving the agent to infer usage based on context alone.

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 the full burden. It describes a read operation ('Get') but doesn't disclose behavioral traits like whether it requires authentication, rate limits, error handling, or the format of returned data. The description adds minimal context beyond the basic purpose, leaving gaps in understanding how the tool behaves in practice.

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 purpose and lists key data elements. There's no wasted text, and it's appropriately sized for a simple tool. However, it could be slightly more structured by separating usage context, but it's still highly 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?

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It covers what the tool does but lacks details on behavioral aspects like data format, errors, or dependencies. Without annotations or output schema, the description should provide more context to fully guide an agent, but it's minimally adequate.

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 input schema has 100% description coverage, with the parameter 'product_url' documented as 'Full URL of the PetSmart product page'. The description doesn't add any meaning beyond this, such as URL format examples or validation rules. With high schema coverage, the baseline score is 3, as the schema adequately handles parameter semantics without extra description input.

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 PetSmart product', listing specific data elements like description, ingredients, reviews, variants, and availability. It distinguishes from siblings like 'search_products' by focusing on a single product rather than searching. However, it doesn't explicitly contrast with all siblings (e.g., 'add_to_cart' is for actions, not retrieval).

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 detailed product information is needed for a specific product, as opposed to 'search_products' for broader queries. However, it lacks explicit guidance on when to use this tool versus alternatives like 'add_to_cart' (which might require product details first) or prerequisites such as having a product URL. No exclusions or clear alternatives are stated.

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 whether it confirms bookings, handles conflicts, requires authentication, or has rate limits. It mentions optional parameters but doesn't explain their impact on behavior.

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?

Two sentences are front-loaded with the core purpose and service examples, with no redundant information. It's efficient, though slightly more detail on behavioral aspects could improve completeness without sacrificing conciseness.

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 tool with 8 parameters, no annotations, and no output schema, the description is adequate but incomplete. It covers the purpose and services, but lacks behavioral context, usage guidelines, and output expectations, leaving gaps for an AI agent.

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 parameters. The description adds minimal value by listing service examples, but doesn't provide additional semantics beyond what's in the schema, such as format details or 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?

The description clearly states the action ('Book a grooming appointment') and resource ('for your pet at PetSmart'), with specific service examples. It distinguishes from siblings like 'schedule_training' by focusing on grooming, though it doesn't explicitly contrast with other scheduling tools.

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 explicit guidance on when to use this tool versus alternatives like 'find_store' for location lookup or 'schedule_training' for other services. The description implies usage for grooming appointments but lacks context about 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?

No annotations are provided, so the description carries the full burden. It mentions booking a class but doesn't disclose behavioral traits such as whether this is a read-only or mutating operation, authentication requirements, rate limits, confirmation processes, or what happens after booking (e.g., email confirmation). For a booking tool with zero annotation coverage, 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 appropriately sized with two sentences: one stating the purpose and one listing class types. It's front-loaded with the core function, and each sentence adds value without waste. However, it could be slightly more structured by explicitly separating purpose from details.

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 complexity (booking tool with 7 parameters, no annotations, no output schema), the description is incomplete. It covers the purpose and class types but lacks behavioral context (e.g., mutation effects, response format) and doesn't leverage sibling tools for guidance. It's adequate as a minimum but has clear gaps for effective agent use.

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 all 7 parameters with clear descriptions. The description adds minimal value beyond the schema by listing example class types, but it doesn't provide additional syntax, format details, or constraints. 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 tool's purpose: 'Book a dog training class at PetSmart.' It specifies the verb ('Book') and resource ('dog training class'), and distinguishes it from siblings like 'schedule_grooming' by focusing on training. However, it doesn't explicitly differentiate from other booking tools (none listed), so it's not a perfect 5.

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 by listing class types ('puppy training, beginner obedience, advanced training, and specialty workshops'), suggesting when to use it based on training needs. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'schedule_grooming' or prerequisites (e.g., dog age requirements), leaving some ambiguity.

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. It discloses that it 'returns a list of matching products with prices, ratings, and URLs', which is useful behavioral context. However, it lacks details on rate limits, authentication needs, pagination behavior beyond the 'page' parameter, or error conditions.

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 concise sentences with zero waste. The first sentence establishes purpose and scope, the second explains the return format. Every word earns its place, and it's 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?

For a search tool with 6 parameters, 100% schema coverage, and no output schema, the description provides adequate purpose and return format. However, it lacks behavioral details like pagination handling, error scenarios, or performance characteristics that would be helpful given the tool's 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?

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for high schema 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 verb 'search' and resource 'pet products on PetSmart', specifying the scope with examples like 'food, toys, supplies, and accessories'. It distinguishes from siblings like 'get_product_details' by focusing on search functionality rather than detailed product information.

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 for searching pet products, but does not explicitly state when to use this tool versus alternatives like 'get_product_details' for specific product info or 'find_store' for physical locations. 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.