Aldi MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information ('Get'), implying a read-only operation, but doesn't address key aspects like error handling (e.g., invalid store IDs), response format, or potential rate limits. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond basic functionality.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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 ('Get operating hours and contact info'), making it easy to parse quickly. Every part of the sentence contributes to understanding, earning its place with zero waste.

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

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

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output expectations. Without annotations or an output schema, the description should do more to explain what information is returned and how to handle errors, but it meets the bare minimum for a simple lookup tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter-specific information beyond what the schema provides. Since schema description coverage is 100% (the 'store_id' parameter is fully documented in the schema), the baseline score is 3. The description doesn't compensate with additional details like format examples or usage tips, but it doesn't need to given the schema's completeness.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 ('operating hours and contact info for a specific Aldi store'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'find_stores' (which likely lists stores) or 'check_product_availability' (which focuses on products), leaving some ambiguity about its unique role in the context of other store-related tools.

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

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

The description provides minimal guidance, only implying usage when store details are needed. It doesn't specify when to use this tool versus alternatives (e.g., 'find_stores' for locating stores or other tools for product info), nor does it mention prerequisites like needing a store ID from 'find_stores' results, which is only hinted at in the schema. This lack of explicit context limits effective tool selection.

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