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illinigirl

Meal Planner MCP

by illinigirl

add_recipes

Add multiple recipes at once to build a personalized recipe library, with ingredient parsing for automated shopping lists.

Instructions

Bulk-add many recipes in one call — the fast way to build a starter library when you DON'T have a Plan to Eat export to import.

The intended flow: generate a batch tailored to the user's tastes (their cuisines, constraints, what they actually cook — don't just produce generic recipes they won't make), let them review it, then save the batch here. The planner only earns its keep over recipes the user genuinely likes.

Each item: {"title": str, "ingredients": [free-text lines], plus optional "servings", "tags", "total_time_min", "cuisine", "course", "directions"}. Ingredient lines are parsed like add_recipe so they feed the shopping-list math. Items missing a title or ingredients are skipped (and reported); ids are de-duplicated against the library and within the batch. One state write for the whole batch. Returns the saved recipes + counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recipesYes
Behavior5/5

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

Discloses item skipping for missing title/ingredients, de-duplication, single state write, and return structure. No annotations present, so description carries full burden.

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?

Efficiently structured with purpose, flow, and details; each sentence adds value without redundancy.

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

Completeness5/5

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

Comprehensively covers purpose, usage, item format, error handling, and return value despite no output schema or annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds detailed field descriptions (title, ingredients, optional fields) and behavior (parsing, de-duplication) beyond the minimal schema, which has 0% coverage.

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?

Clearly states 'Bulk-add many recipes in one call' with specific use case (building a starter library) and distinguishes from sibling tools like add_recipe and import_recipes.

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

Usage Guidelines5/5

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

Describes when to use (no Plan to Eat export) and the intended flow (generate, review, save), with explicit exclusions and alternative tool mention.

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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