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cyntrica

Gov Data MCP

by cyntrica

dol_ui_claims_national

Read-only

Fetch national weekly UI claims (initial and continued) with insured unemployment rate and covered employment to monitor labor market stress.

Instructions

Get national weekly Unemployment Insurance (UI) initial and continued claims. Includes insured unemployment rate and covered employment. Key economic indicator — spikes indicate labor market stress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of weekly records (default 25, use 52 for 1 year)
offsetNoPagination offset
sort_byNoField to sort by: 'rptdate' (default)
sort_orderNoSort direction (default: desc)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The readOnlyHint annotation covers the safety profile, and the description adds useful context: the included metrics (insured unemployment rate, covered employment) and the interpretation (spikes indicate stress). No contradictory behavior is disclosed. It stops short of describing pagination or data formatting, but those are partially covered by the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, front-loaded sentences each add value: what the tool gets, what extra metrics it includes, and how to interpret the data. No fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the purpose, key data elements, and economic significance. While there is no output schema, the description mentions the main outputs (claims, rate, employment). Pagination and sorting are covered by the schema. It could be more explicit about common use cases or data quirks, but overall it is sufficient for an agent to select and call the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already handles parameter meaning. The description adds no further parameter-level detail beyond the 'weekly' context, which is also in the schema's limit description. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Get national weekly Unemployment Insurance (UI) initial and continued claims' – a specific verb, resource, and scope. It clearly differentiates from the sibling 'dol_ui_claims_state' by explicitly stating 'national'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clear context is provided: it is a national indicator used to gauge labor market stress. However, it doesn't explicitly tell the agent to use the state-level sibling for state-level data, and no when-not-to-use guidance is given. The widespread sibling naming convention makes the alternative obvious, so a small deduction is appropriate.

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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