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check_product_availability

Verify product availability at a specific Aldi store by providing product and store IDs to confirm stock status before shopping.

Instructions

Check whether a product is available at a specific Aldi store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYesThe product ID to check
store_idYesThe store ID to check availability at
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 checking availability but does not describe what 'available' means (e.g., in-stock, online, limited quantity), potential rate limits, authentication needs, error conditions, or the format of the response. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse and understand quickly. Every part of the sentence earns its place by contributing essential information.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete for a tool that performs a query operation. It does not explain what the return value will be (e.g., boolean, stock level, error messages) or any behavioral nuances like caching or data freshness. For a tool with no structured output information, the description should provide more context to be fully helpful.

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?

The schema description coverage is 100%, with both parameters ('product_id' and 'store_id') clearly documented in the input schema. The description does not add any additional meaning beyond what the schema provides, such as explaining how to obtain these IDs or their expected formats. Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Check whether a product is available') and the resource ('at a specific Aldi store'), distinguishing it from sibling tools like 'get_product_details' or 'search_products' which focus on product information rather than availability. It uses precise language that directly communicates the tool's function without ambiguity.

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 when you need to verify product availability at a particular store, but it does not explicitly state when to use this tool versus alternatives like 'search_products' or 'get_product_details'. There is no guidance on prerequisites, exclusions, or specific scenarios, leaving the agent to infer context from the tool name and description alone.

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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