Cheapest Grocery Basket

Compare one grocery item across nearby stores

find_product

Compare a single grocery item across every collected store in a ZIP. Returns each store's actual current shelf price, whether it is on sale (and the regular price), the package size, the price normalized per comparable unit, stock, a purchase link, and when that price was last read. Use this to answer "who has the cheapest milk near me" — and note the answer reports BOTH the lowest sticker price and the best value per unit, which frequently disagree because the cheap sticker is a smaller package. For a whole shopping list use price_basket or cheapest_basket instead; calling this per item costs more and cannot optimize across stores. Costs $0.005 USDC per call via x402 on Base.

Input Schema

TableJSON Schema

Name	Required	Description
`q`	Yes	The item to price, in ordinary shopper language, e.g. 'milk', 'eggs', 'ground beef'.
`zip`	Yes	5-digit US ZIP code to price against, e.g. '30501'. Coverage is per collected ZIP; an uncovered ZIP returns an explicit error and is not charged.
`stores`	No	Optional comma-separated chains to restrict to, e.g. 'aldi,publix'. Omit to compare every collected store.
`maxAgeDays`	No	Optional freshness limit in days (default 14, max 120). A price read longer ago than this is withheld rather than returned as if current; raise it to accept older readings.

TDQS

A4.5/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It does substantial work by disclosing the returned data points, the sale/regular price distinction, unit-price normalization, stock, purchase links, price freshness, and the caveat that lowest sticker price often differs from best value per unit. It does not describe response ordering or error response shape, so it is strong but not exhaustive.

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?

Every sentence earns its place: purpose, return contract, canonical use case with a caveat, alternative routing, and cost are each stated once without redundancy. The most decision-relevant information is front-loaded.

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?

Despite having no output schema and no annotations, the description supplies enough for an agent to select, invoke, and interpret the result: scope, return fields, the unit-price nuance, alternative tools, and per-call cost. No critical operational fact is missing for this low-complexity tool.

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 coverage is 100%, so the schema fully documents all four parameters. The description adds useful context about the item being singular and the per-call cost, but it does not add parameter syntax, defaults, or format details beyond what the input schema already provides. Baseline 3 is appropriate.

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 opening sentence names a specific verb ('Compare'), resource ('a single grocery item'), and scope ('across every collected store in a ZIP'), which clearly differentiates it from basket-level siblings. The title and description align, and the enumerated return fields make the purpose explicit.

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?

It gives a concrete canonical use case ('who has the cheapest milk near me') and explicitly names alternatives for other cases ('For a whole shopping list use price_basket or cheapest_basket'), including the cost and optimization rationale. This removes ambiguity about when to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Cheapest Grocery Basket tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0

Disambiguation4/5

find_product, demand_report, and request_data are clearly distinct, but price_basket and cheapest_basket both operate on a whole shopping list. Their descriptions define different output styles (itemized per-store baskets vs. optimized buying decision), so an agent can usually choose correctly, though some overlap remains.

Naming Consistency4/5

All names are lowercase snake_case and descriptive, but find_product, price_basket, and request_data follow a verb_noun form while cheapest_basket and demand_report are noun phrases. This is a minor inconsistency rather than a chaotic naming scheme.

Tool Count4/5

The four listed tools are well-scoped for grocery price/basket queries plus data demand. However, the header declares five tools while only four are described, so the exact intended surface is slightly uncertain.

Completeness4/5

Core grocery use cases are covered: single-item lookup, one-trip basket pricing, multi-store optimization, and data demand. A minor gap is the lack of dedicated tooling for broader store or product meta-information beyond the price and stock fields already returned.

Resources

Need Help?