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Find recipes

find_recipes
Read-onlyIdempotent

Use this to find drink and food recipes from the teas.co.uk recipe library, such as iced teas, lattes, chai or baking with tea. Give query (the kind of recipe in plain words), product_id (from find_products, for recipes that use that product) or both; with both, recipes that use the product and match the words rank first, and a call with neither is refused. limit is 1 to 10 (default 5) and there is no paging: the best matches come first, each with its type, prep time, up to three teas.co.uk products it uses and a link, and an empty list means nothing matched. Drinks made with alcohol are never included. To find products to buy use find_products.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many recipes (default 5).
queryNoWhat kind of recipe, for example "iced peach tea" or "chai latte".
product_idNoOptional product id from find_products.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
recipesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare the read-only, idempotent, non-destructive safety profile, so the description is free to add policy detail instead — and it does: no paging, limit capped at 10 with a default of 5, best matches first, and an explicit content exclusion (alcohol-based drinks are never returned). The only unmapped area is anything about auth or rate limits, which is not relevant for a public library search.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then parameter guidance, then ranking and output expectations, then the sibling redirect. It is a single dense paragraph that reads well, though the return-value enumeration is partly redundant given an output schema exists.

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?

An output schema exists, so the description need not document the return shape, yet it still covers ranking order, the refusal case, limit bounds, absence of paging, and content exclusions. An agent has everything needed to call this correctly on the first attempt.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description goes beyond the schema by explaining the semantics of supplying both query and product_id (ranked first) and that 'limit' interacts with the no-paging behavior. That is genuine added meaning rather than restatement.

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?

Opens with a specific verb and resource ("find drink and food recipes from the teas.co.uk recipe library") and gives concrete examples like iced teas, lattes, chai and baking with tea. It also explicitly distinguishes itself from the sibling find_products.

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?

States exactly how to select it: give query, product_id, or both, explains the ranking when both are supplied, and notes that a call with neither is refused. It also routes the agent away with "To find products to buy use find_products."

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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