list_capabilities
Lists coverage (how many states, counties and cities), the date the data was last checked, and related Nero Labs Rules servers. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Lists coverage (how many states, counties and cities), the date the data was last checked, and related Nero Labs Rules servers. Free.
| 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?
No annotations are provided, so the description carries the full behavioral burden. It adds useful context by stating the tool is free and that the returned data includes a 'last checked' date (implying freshness), but it omits other behavioral details such as read-only safety, authentication requirements, or rate limits. This is adequate but not comprehensive for the no-annotation case.
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 front-loads the core purpose ('Lists coverage') and then adds the key details without any wasted words. It is appropriately sized for a simple list tool.
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 low complexity (zero parameters, no output schema, no annotations), the description is nearly complete: it explains what is returned and notes the tool is free. It could be slightly richer by stating that it is a read-only discovery operation or suggesting when to call it, but for a simple capability listing it provides enough context to use correctly.
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 there is no parameter semantics to compensate for. The baseline for zero parameters is 4, and the description appropriately does not need to discuss inputs.
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 (Lists) and resource (coverage) and details exactly what is returned: state/county/city counts, last-checked date, and related Nero Labs Rules servers. It is clear what the tool does, but it does not explicitly differentiate itself from the sibling wage-query tools (get_minimum_wage, list_upcoming_minimum_wage_changes), so it falls short of a 5.
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 guidance on when to use this tool versus alternatives. The description never mentions the sibling tools, nor does it suggest contexts such as 'call this first to discover available coverage before querying wages.' It only describes what the tool returns.
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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