get_unemployment_rateFetches the BLS unemployment rate for a specified area, defaulting to US, as a typed JSON snapshot for public statistics.
Return BLS unemployment rate for an area code.
| Name | Required | Description | Default |
|---|---|---|---|
| area | No | US |
| 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?
No annotations provided, so the description carries full burden. It states the data source (BLS) but discloses nothing about return format, data recency, caching, or error behavior for an unknown area.
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?
A single efficient sentence with no waste and the key information front-loaded. Could afford to add a brief parameter hint without bloat.
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?
An output schema exists so return values need not be explained, but the 0% parameter coverage and absent annotations leave the caller guessing about the 'area' input and the safety profile.
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?
Schema coverage is 0% and the description does not explain the 'area' parameter, its format, valid values, or what the 'US' default means. With low coverage, the description should compensate but does not.
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?
States a specific verb (return) and resource (BLS unemployment rate). Does not distinguish from siblings like get_cpi or get_fred_series, but the resource name is self-evidently distinct.
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?
No when-to-use guidance, no mention of alternatives, no exclusions. An agent must infer context entirely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.