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FridgeToForks

Find recipes from what is in the fridge

find_recipes_from_ingredients

Search 100,000+ real recipes for ones that can be cooked from a given list of ingredients, and say exactly what is MISSING from each. Common cupboard staples (salt, oil, flour, common spices and 380 others) are assumed to be on hand and are never reported as missing. Results are ranked by how much of the given list a recipe uses minus how many extra items it would require the cook to buy, so the top result is the one that needs the fewest trips to a shop. Use this whenever someone asks what they can make from ingredients they already have.

Input Schema

NameRequiredDescriptionDefault
ingredientsYesWhat the cook has, e.g. ["chicken thighs","rice","half an onion"]. Free text per item is fine; quantities are ignored.
max_resultsNoHow many recipes to return (1-12, default 6).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses the dataset size, the non-obvious staple assumption (salt, oil, flour, spices and 380 others are never reported missing), what output includes (what is MISSING), and the exact ranking formula. It still omits operational details like rate limits, latency, or authentication requirements.

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 purpose is front-loaded, and every sentence adds useful information: dataset scope, staple assumption, missing-item reporting, ranking logic, and a usage trigger. There is no redundancy or filler.

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

Completeness4/5

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

For a two-parameter read tool with no annotations and no output schema, the description is quite complete on behavior, assumptions, and ranking. It is slightly thin on the exact return structure and on how to proceed from results to full recipe details, which the sibling tool could cover.

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?

Schema description coverage is 100% and the schema already explains that ingredients are free text with quantities ignored, and that max_results is 1-12 with default 6. The description adds result-semantics context (staples not counted as missing) but little parameter-specific meaning beyond what the schema already provides, so the baseline 3 applies.

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 states a specific verb and resource with scope: 'Search 100,000+ real recipes for ones that can be cooked from a given list of ingredients.' This is unambiguous against the sibling get_recipe_details, but it never explicitly names or contrasts with that sibling, so the differentiation is implicit rather than stated.

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?

It gives a clear trigger: 'Use this whenever someone asks what they can make from ingredients they already have.' However, it offers no exclusions, alternatives, or prerequisites (e.g., redirecting to get_recipe_details for full instructions), so it stops short of full when/when-not guidance.

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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