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Symfomany

Recettes MCP Server

by Symfomany

generate_recipe_from_ingredients

Create Christmas recipes using available ingredients. This tool helps you make festive meals from what you have on hand.

Instructions

Generates a new Christmas recipe from a list of ingredients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ingredientsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:240-254 (handler)
    The async handler function implementing the tool logic: generates a simple hardcoded Christmas recipe using the provided ingredients list.
    async def generate_recipe_from_ingredients(ingredients: List[str]) -> Dict:
        """Génère une nouvelle recette de Noël à partir d'une liste d'ingrédients."""
        return {
            "name": "Recette créative de Noël",
            "category": "Plat principal",
            "servings": 4,
            "ingredients": {ingredient: "quantité au goût" for ingredient in ingredients},
            "instructions": [
                "Préchauffer le four à 180°C.",
                "Mélanger tous les ingrédients dans un plat.",
                "Enfourner pour 30 minutes.",
                "Déguster avec amour.",
            ],
            "wine_pairing": "Un vin qui vous fait plaisir !",
        }
  • main.py:236-239 (registration)
    The @mcp.tool decorator registering the handler function with the MCP server.
    @mcp.tool(
        name="generate_recipe_from_ingredients",
        description="Generates a new Christmas recipe from a list of ingredients.",
    )
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 the tool generates a recipe, implying a creation operation, but doesn't disclose any behavioral traits such as whether it's deterministic, requires authentication, has rate limits, or what the output format is. This is a significant gap for a tool with no annotation coverage.

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 any wasted words. It's appropriately sized for the tool's complexity, making it easy for an agent to parse quickly.

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 has an output schema (which covers return values), no annotations, and low parameter schema coverage, the description is minimally adequate. It states what the tool does but lacks behavioral context and usage guidance, making it incomplete for optimal agent operation without additional structured data.

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 input schema has 1 parameter with 0% description coverage, and the description adds some meaning by specifying that the parameter is a 'list of ingredients'. However, it doesn't provide details on format, constraints, or examples, so it only partially compensates for the low schema coverage, aligning with the baseline expectation.

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 with a specific verb ('generates') and resource ('new Christmas recipe'), and specifies the input ('from a list of ingredients'). However, it doesn't explicitly distinguish this tool from similar siblings like 'invent_recipe' or 'invent_magical_recipe', which might also generate recipes, so it doesn't fully achieve sibling differentiation.

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 any prerequisites, exclusions, or compare it to other recipe-generation tools in the sibling list, such as 'invent_recipe' or 'get_random_recipe', leaving the agent without context for selection.

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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