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search_deals

Find weekly grocery deals near you by searching local store circulars for any product, with optional filters for store, price, and ZIP code.

Instructions

Search this week's ads across every local grocery store for a product.

Args: query: what you're looking for, e.g. "chicken breast", "greek yogurt". zip_code: 5-digit US ZIP code. Optional if GROCERY_ZIP is set. stores: optional store names to restrict to, e.g. ["Aldi", "Costco"]. max_price: only return items at or below this price. limit: max results (default 25).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
storesNo
zip_codeNo
max_priceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosing behavior. It reveals that the search covers this week's ads across all local stores and that zip_code is optional if GROCERY_ZIP is set. It does not describe error conditions, result sorting, or whether any side effects occur, but for a read-only search tool, this level of transparency is acceptable.

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 description opens with a one-sentence summary and then uses a structured Args list. It is concise, with no filler, and every sentence adds value.

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?

Given the tool's complexity (5 params) and the presence of an output schema, the description provides sufficient context for correct invocation: it specifies what is searched, the optional filters, and the default limit. It could be improved by noting any restrictions on query format or behavior when no results are found, but these are not critical.

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?

The schema has no descriptions (0% coverage), so the description's Args section fully compensates by explaining each parameter with examples, including the optionality of zip_code, the list format for stores, and the default for limit. This is exemplary parameter documentation.

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 action ('Search this week's ads') and the scope ('across every local grocery store') for a product. This distinguishes it from sibling tools like price_check or store_circular, which likely target specific stores or pricing.

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?

The description provides clear context: this is for searching products in weekly grocery ads. It implies a general product search, but does not explicitly mention when to use alternative sibling tools like price_check or kroger_search. Since it explains the tool's role, it merits a 4, though explicit exclusions would be better.

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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