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build_grocery_list

Resolve a grocery list to real products at one store. Send the complete list of items and quantities each call.

Instructions

Resolve a grocery/pantry list to real products at one store (raw ingredients only — NOT restaurant food). STATELESS: every call REPLACES the list, so always send the complete list. Weight items take decimal quantity (0.5 = half lb) only when purchase_type is MEASUREMENT; eggs are per dozen. Verify resolved items[].name with the user before carting. Vague asks: cap at 20 items and show your picks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes[{"name":"milk"},{"name":"ground beef","quantity":0.5}]
intentYesOne short line stating who this is for and the goal, e.g. 'Help the user order dinner'. DO NOT include the user's verbatim words, dietary/health/religious details, budgets, names, or other personal specifics — a generic goal is expected.
servingsNoOnly when the user says 'for N people' — display-only
store_idNoPin to a store (takes precedence over desired_mx_name)
desired_mx_nameNoPreferred merchant name, e.g. 'Whole Foods'
Behavior4/5

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

Annotations indicate write operation (readOnlyHint=false) and interactive (openWorldHint=true). Description adds stateless behavior, input rules for quantity, and verification step with user, providing context beyond annotations.

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?

Description is a single paragraph but packs essential information without fluff. Could be better structured with bullet points, but remains concise and readable.

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?

Despite no output schema, the description covers statefulness, input format, quantity rules, verification, and vague ask handling. No major gaps for a 5-parameter tool with good annotations.

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%, but description adds extra meaning: items example format, quantity decimal rule tied to purchase_type (though not in schema), and intent field guidelines. Adds value beyond schema descriptions.

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 resolves a grocery/pantry list to real products at one store, raw ingredients only. It distinguishes from sibling tools like search_restaurants and get_menu by specifying 'NOT restaurant food'.

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?

Explicitly states the tool is stateless and replaces the list, requiring the complete list each time. Also provides guidance for vague asks to cap at 20 items and show picks, but does not explicitly list alternative tools.

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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