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get_weekly_specials

Retrieve current weekly special deals and ALDI Finds for specific stores or regions, with optional filtering by product categories.

Instructions

Get current weekly special deals and ALDI Finds for a given store or region.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idNoOptional store ID to get location-specific specials
categoryNoOptional category to filter specials (e.g. 'produce', 'meat', 'aldi-finds')
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool retrieves 'current' deals, implying real-time or recent data, but doesn't specify whether this is a read-only operation, requires authentication, has rate limits, or what the output format looks like (e.g., list of items, prices, dates). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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 is a single, well-structured sentence that efficiently conveys the core purpose and key parameters without any wasted words. It is front-loaded with the main action ('Get current weekly special deals and ALDI Finds') and directly addresses the tool's scope, making it easy to parse and understand quickly.

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

Completeness3/5

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

Given the tool's moderate complexity (2 optional parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameter intent, but lacks details on behavioral traits (e.g., read-only status, error handling) and output format, which are important for an agent to use it correctly. Without annotations or an output schema, the description should do more to compensate, but it meets a minimum viable standard.

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%, meaning the input schema already fully documents the two optional parameters ('store_id' and 'category') with clear descriptions. The description adds marginal value by implying these parameters filter results ('for a given store or region' and 'category to filter specials'), but it doesn't provide additional syntax, format details, or examples beyond what the schema states. With high schema coverage, the baseline score of 3 is appropriate.

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 clearly states the tool's purpose with a specific verb ('Get') and resource ('weekly special deals and ALDI Finds'), making it immediately understandable. It distinguishes itself from siblings like 'check_product_availability' or 'search_products' by focusing on promotional items rather than general inventory or product searches. However, it doesn't explicitly contrast with all siblings (e.g., 'get_product_details' might overlap in some contexts).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'for a given store or region,' which suggests when to use this tool versus alternatives that might not be location-specific. However, it lacks explicit guidance on when to choose this over siblings like 'search_products' (which might also find specials) or 'check_product_availability' (which could check stock for special items), and it doesn't mention prerequisites or exclusions.

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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