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.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details such as data freshness, permissions, rate limits, or side effects. It only lists available series without disclosing any constraints or error conditions.
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, front-loaded sentence with no extraneous words. It effectively communicates the core purpose but could be slightly more structured.
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 simple tool (2 parameters, no output schema), the description covers the data sources and options. However, it omits output format, time range context for the months parameter, and any usage hints, leaving some gaps.
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 description coverage is 100%, so baseline is 3. The description repeats the series options in natural language, adding minor reinforcement but no new meaning beyond what the parameter descriptions already provide.
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 explicitly states the tool retrieves U.S. labor market data from BLS and lists specific data types (unemployment rate, nonfarm payrolls, etc.). The verb 'get' clearly indicates action, and sibling tools cover other economic domains (e.g., energy, inflation), distinguishing this tool for labor metrics.
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?
Description implies usage for labor market data but does not explicitly guide when to use this tool versus alternatives. No exclusion criteria or comparison to sibling tools like get_inflation or get_macro are provided.
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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