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 search capability but doesn't describe key behaviors: whether this is a read-only operation, how results are returned (e.g., list format, pagination), error handling, or any rate limits. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is concise and front-loaded with the core purpose in the first sentence. The second sentence adds useful context about search parameters. Both sentences earn their place, and there's no wasted text. However, it could be slightly more structured (e.g., explicitly listing behaviors).

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), no annotations, and no output schema, the description is minimally adequate. It covers the purpose and basic usage but lacks details on behavior, return values, and error handling. For a search tool, this leaves the agent with incomplete information, though the schema helps with parameters.

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 limit) with clear descriptions. The description adds marginal value by mentioning 'city, state, or keyword' for the query parameter, but this is largely redundant with the schema's description. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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 Shake Shack restaurant locations' specifies the verb (find) and resource (locations). It distinguishes from siblings like get_location_details (which likely retrieves details for a specific location) and search_menu (which searches menu items). However, it doesn't explicitly differentiate from all siblings (e.g., get_featured_items might also involve locations).

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 some usage context by stating 'Can search by city, state, or keyword,' which implies when to use this tool (for location searches). However, it doesn't explicitly state when to use alternatives (e.g., use get_location_details for specific location info, search_menu for menu items) or any exclusions (e.g., not for ordering). The guidance is implied but not comprehensive.

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 states the tool retrieves data ('Get'), implying a read-only operation, but doesn't address other traits like authentication needs, rate limits, error handling, or data freshness (e.g., how 'current' is defined). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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?

The description is a single, efficient sentence that front-loads the core purpose ('Get current featured, seasonal, or limited-time menu items') and specifies the context ('at Shake Shack'). Every word earns its place, with no redundancy or unnecessary elaboration, 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?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the what and where but lacks details on behavioral aspects like data format, error cases, or freshness guarantees. Without annotations or output schema, more context on what 'Get' returns would improve completeness, but it's not entirely inadequate for a basic read operation.

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 0 parameters with 100% description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for 0 parameters, as there's nothing to compensate for, and the description doesn't detract from the schema's completeness.

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: 'Get current featured, seasonal, or limited-time menu items at Shake Shack.' It uses a specific verb ('Get') and identifies the resource ('featured, seasonal, or limited-time menu items'), distinguishing it from siblings like 'get_menu' (general menu) and 'search_menu' (searchable menu). However, it doesn't explicitly contrast with 'get_menu' beyond implying a subset focus.

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 context by specifying 'featured, seasonal, or limited-time' items, suggesting this tool is for promotional or time-sensitive content rather than the full menu. However, it lacks explicit guidance on when to use this versus 'get_menu' or 'search_menu' (e.g., no 'when-not' statements or named alternatives), leaving some ambiguity for the agent.

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 states this is a 'Get' operation, implying it's likely read-only, but doesn't confirm this or describe other traits like error handling, rate limits, authentication needs, or what 'detailed information' entails in the response. This leaves significant gaps for an agent to understand the tool's 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?

The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 for a tool that presumably returns detailed information. It doesn't explain what 'detailed information' includes (e.g., address, hours, menu items), leaving the agent uncertain about the response format and content, which is a significant gap for effective tool 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?

The schema description coverage is 100%, with the single parameter 'location_id' fully documented in the schema (including an example). The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or usage context, so it meets the baseline score 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 action ('Get detailed information') and resource ('about a specific Shake Shack location by ID'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'find_locations' or 'get_ordering_info', which might also provide location-related information, so it doesn't reach the highest 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. It doesn't mention what 'detailed information' includes compared to other tools (e.g., 'find_locations' might list locations, 'get_ordering_info' might provide ordering details), nor does it specify prerequisites or exclusions for usage.

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 states what the tool does but doesn't describe important behavioral aspects like whether this is a read-only operation, what format the menu data returns, if there are rate limits, authentication requirements, or error conditions. The description is minimal and 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 appropriately concise with two clear sentences that efficiently communicate the core functionality. It's front-loaded with the main purpose and follows with parameter context. There's no wasted language, though it could be slightly more structured for optimal agent comprehension.

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 no annotations and no output schema, the description is incomplete for a data retrieval tool. It doesn't explain what the return value contains (menu items with prices? descriptions? images?), how data is structured, or any limitations. For a tool that presumably returns complex menu data, this leaves significant gaps in understanding how to effectively use the tool.

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 fully documents the single optional parameter with its description and available values. The description adds marginal value by mentioning 'Can return all categories or a specific category', which reinforces the parameter's purpose but doesn't provide additional semantic context beyond what the schema already states.

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: 'Get the Shake Shack menu' specifies the verb (get) and resource (menu). It distinguishes from some siblings like 'find_locations' or 'get_nutrition_info', but doesn't explicitly differentiate from 'search_menu' which might have overlapping functionality.

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 implied usage guidance by mentioning 'Can return all categories or a specific category', which suggests when to use the optional parameter. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_menu' or 'get_featured_items', leaving the agent to infer based on tool names 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 of behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't specify if this is a read-only operation, what format the nutritional information returns (e.g., calories, allergens list), whether it requires authentication, or if there are rate limits. For a 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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states the tool's function ('Get nutritional information and allergen details') and scope ('for Shake Shack menu items'), with zero waste or redundancy. This is appropriately sized for a simple tool.

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 output schema, no annotations), the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral context (e.g., read-only nature, return format) and usage guidelines. Without annotations or output schema, the description should do more to compensate, but it only meets the minimum viable threshold.

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 adds no parameter-specific information beyond what the input schema provides. The schema has 100% description coverage, with the 'item_name' parameter clearly documented as 'Name of the menu item to get nutrition info for (e.g. 'ShackBurger', 'Fries').' The description doesn't elaborate on parameter semantics, such as valid item names or formatting, so it meets the baseline 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 tool's purpose: 'Get nutritional information and allergen details for Shake Shack menu items.' It specifies the action ('Get') and resource ('Shake Shack menu items'), and distinguishes itself from siblings like 'get_menu' or 'search_menu' by focusing on nutrition/allergen data. However, it doesn't explicitly contrast with all siblings (e.g., 'get_featured_items' might also return nutritional info).

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 doesn't mention when this tool is appropriate compared to 'get_menu' (which might include nutrition info) or 'search_menu' (which might filter by nutritional criteria). There's no context about prerequisites, limitations, or typical use cases beyond the basic purpose.

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 states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits such as authentication needs, rate limits, error conditions, or what format the information is returned in (e.g., text, links, structured data).

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 ('Get information about how to order at Shake Shack') and adds clarifying examples without unnecessary detail. Every word 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?

Given the tool has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects (e.g., response format, errors) that would be needed for full contextual understanding, especially since it's a read operation with potential complexity in output.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying the scope ('how to order at Shake Shack') and examples ('app, kiosk, online, etc.'), which clarifies what information will be retrieved beyond just the tool name.

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: 'Get information about how to order at Shake Shack' with specific examples (app, kiosk, online). It uses a specific verb ('Get') and resource ('ordering information'), but doesn't explicitly distinguish it from sibling tools like 'get_menu' or 'search_menu' which might also relate to ordering.

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 doesn't mention prerequisites, context for usage, or differentiate from siblings like 'get_menu' (which might include ordering details) or 'find_locations' (which could relate to in-person ordering).

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 states the tool searches for items matching a query but doesn't describe what the search returns (e.g., list of items, details), how results are ordered, if there are limits, or error conditions. This leaves significant gaps for a search 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 with zero waste—it directly states the tool's action and target. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 no annotations and no output schema, the description is incomplete for a search tool. It doesn't explain what the tool returns (e.g., item names, details, or just IDs), potential limitations, or how to handle no results. This leaves the agent with insufficient context to use the tool effectively.

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 parameter 'query' well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as search syntax or examples not already covered. Baseline 3 is appropriate since 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 with a specific verb ('Search') and resource ('Shake Shack menu'), and distinguishes it from siblings like 'get_menu' by specifying search functionality. However, it doesn't explicitly differentiate from 'get_featured_items' or 'get_nutrition_info' in terms of search vs. 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 provides no guidance on when to use this tool versus alternatives like 'get_menu' (which might retrieve the full menu) or 'get_featured_items' (which might show highlighted items). It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.

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