Get U.S. labor market data from BLS. Unemployment rate, nonfarm payrolls, job openings, and wages.
| Name | Required | Description | Default |
|---|---|---|---|
| months | No | Months of history | |
| series | No | unemployment_rate (default), nonfarm_payrolls, job_openings, avg_hourly_earnings, labor_force_participation | unemployment_rate |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only mentions the data source (BLS) but omits details about mutability, data freshness, rate limits, or response format. A score of 2 reflects this significant gap.
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 extremely concise—two sentences with no filler. The first sentence front-loads the purpose, and the second lists key data types. Every word earns its place, making it highly efficient for an AI agent.
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 simplicity of the tool (2 parameters, no output schema) and the sibling context, the description is mostly complete. It fails to hint at the response format (e.g., JSON), but this is minor for a straightforward data retrieval tool. A score of 4 reflects minor omission.
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 100%, so the baseline is 3. The description adds minimal value beyond the schema, merely listing available data types which the schema already enumerates in the 'series' parameter description. No further semantic enrichment is offered.
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 clearly states the tool gets U.S. labor market data from BLS and lists specific data types (unemployment rate, nonfarm payrolls, etc.), making the verb and resource unambiguous. It effectively distinguishes from sibling tools like get_inflation and get_treasury by specifying the labor market domain.
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 provides clear context that the tool is for U.S. labor market data, which implicitly guides when to use it vs. siblings focusing on other economic indicators. However, it lacks explicit exclusions or alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct economic domain (e.g., demographics, inflation, jobs) with no overlap. The descriptions clearly differentiate the data sources and use cases.
All tools follow a consistent `get_<topic>` pattern using snake_case, making the naming predictable and easy to navigate.
With 7 tools, the server provides a focused yet comprehensive set of macroeconomic indicators without being overwhelming. Each tool serves a clear purpose.
Covers major macroeconomic areas (employment, inflation, GDP, demographics, energy, treasury) but lacks minor categories like trade or consumer confidence. Gaps are slight.