list_locationsList all office locations with country, timezone, and headcount, and return the date range of the data to help focus attendance analysis on available sites.
List every site with its country, timezone and headcount. Also returns the date range the data covers.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by stating the returned fields including the date range, which goes beyond the annotations. There is no contradiction or missing behavioral context.
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?
Two concise, front-loaded sentences deliver all necessary information without waste. The first sentence states the core purpose and fields; the second adds a useful output detail (date range). No filler or redundant language.
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 parameterless tool with no output schema, the description provides the essential information: the full set of data returned (every site, country, timezone, headcount, date range). This is sufficient for an agent to call and interpret the result without further clarification.
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 the schema coverage is effectively 100% and the baseline is 4. The description correctly focuses on the output, adding no parameter details because none are needed. It fully leverages the no-parameter structure.
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 states a specific verb ('List') and resource ('every site') with additional detail on the fields returned (country, timezone, headcount, date range). This clearly distinguishes it from siblings like location_trends or employee_attendance, which suggest different data views.
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 implies a clear use case—obtain a complete list of sites with their metadata—but it does not explicitly mention when to choose this tool over alternatives, provide exclusions, or reference sibling tools. The guidance is adequate but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.