Get locations
get_locationsOffice location details for the Sugarhouse / Salt Lake City office, including address, hours, phone, and service area.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_locationsOffice location details for the Sugarhouse / Salt Lake City office, including address, hours, phone, and service area.
| 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, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description contributes beyond that by specifying exactly what data comes back (address, hours, phone, service area), which matters because there is no output schema.
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?
One sentence, front-loaded with the resource and scoped instance, then the returned fields. No filler or redundancy.
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?
With no output schema and no parameters, the description carries the burden of describing the return payload and does so by enumerating the fields. It is nearly complete; only a note on whether the response can cover multiple offices would add value.
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 takes zero parameters, so the baseline is 4. There is nothing for the description to clarify about argument semantics, and schema coverage is 100%.
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 names the resource (office location details) and the specific instance (Sugarhouse / Salt Lake City office), then enumerates the returned fields (address, hours, phone, service area). This clearly separates it from siblings like get_business_info, get_practice_info, and get_services.
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 content listing implies when to reach for this tool (when you need address, hours, phone, or service area), but there is no explicit when-to-use/when-not statement and no sibling is named as an alternative. Usage is inferable rather than stated.
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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