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markswendsen-code

@striderlabs/mcp-shakeshack

get_nutrition_info

Retrieve nutritional facts and allergen information for Shake Shack menu items to make informed dietary choices.

Instructions

Get nutritional information and allergen details for Shake Shack menu items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
item_nameYesName of the menu item to get nutrition info for (e.g. 'ShackBurger', 'Fries')
Behavior2/5

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.

Conciseness5/5

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.

Completeness3/5

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.

Parameters3/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

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