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generate_recipe

Generate a custom recipe from a natural language description, adapting to dietary restrictions, allergies, and nutritional targets like calories and protein.

Instructions

Generate a new recipe based on natural language instructions and dietary preferences

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesNatural language description of the desired recipe
proteinNoTarget protein in grams per serving (e.g., '30')
caloriesNoTarget calories per serving (e.g., '500')
dislikesNoFoods the user doesn't like
servingsNoNumber of servings (1-20, default: 4)
allergiesNoIngredients to avoid due to allergies
dietaryRestrictionsNoDietary restrictions (e.g., vegetarian, vegan, gluten-free)
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states the tool generates a recipe, without mentioning return format, dependencies, side effects, or error conditions. This is a significant transparency gap.

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 concise sentence that clearly states the tool's function. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description should provide more context about return values and limitations. It only states the tool generates a recipe, leaving the agent unaware of output structure and other behavioral details. The sibling tool adds a need for distinguishing guidance, which is absent.

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 schema provides complete descriptions for all 7 parameters, so the description doesn't need to explain them. The description's mention of 'natural language instructions and dietary preferences' adds a high-level summary but no additional semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a new recipe, using a specific verb and resource. It distinguishes from the sibling 'transform_recipe' by implying creation rather than modification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly indicates the tool is for generating new recipes from user preferences, providing clear usage context. It does not explicitly mention alternatives or exclusions, but the sibling name 'transform_recipe' helps distinguish, so no explicit guidance is required.

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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