Store information
store_infoShop address, phone, opening hours, delivery, returns, graded stock, price match and how to buy.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
store_infoShop address, phone, opening hours, delivery, returns, graded stock, price match and how to buy.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds the information scope. However, it does not disclose whether the information is static or current, what the response format is, or any limitations, so it adds only modest behavioral context beyond the annotations.
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 single-sentence topic list is efficient and front-loads common needs such as address, phone, and opening hours. It is concise but is a sentence fragment without an explicit verb, which slightly weakens structure.
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?
For a zero-parameter, read-only tool without an output schema, the description gives a useful topic list but not the return structure or whether delivery and stock details are static versus live. It is adequate for a simple lookup but leaves some ambiguity relative to check_delivery.
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 tool has zero parameters, so parameter semantics are trivial and the baseline is 4. The description does not need to explain parameter meaning because no inputs exist.
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 enumerates specific store information topics (address, phone, hours, delivery, returns, graded stock, price match, how to buy), making the resource clear. It lacks an explicit verb such as 'returns' and does not distinguish this static information tool from the dynamic sibling check_delivery, so it is clear but not sibling-differentiating.
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?
There is no explicit when-to-use or when-not-to-use guidance. The agent must infer from the topic list that this is for general store FAQ questions, and the description does not tell it when to prefer check_delivery or get_product instead.
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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