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WARN Firehose — Labor Market Intelligence

export_records

Export WARN records in bulk. Requires Pro tier or higher.

Returns up to 500 records with full field details. For CSV/Parquet
downloads, use the REST API at /api/export/.
Get your API key at laborcurrent.com/account

Args:
    api_key: Your LaborCurrent API key (Pro tier required)
    state: Optional 2-letter state code filter
    company: Optional company name filter (partial match)
    days: Look back this many days (default 90, max 730)
    limit: Max records to return (default 100, max 500)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
limitNo
stateNo
api_keyYes
companyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return limit ('up to 500 records'), full field details, and API key requirement. However, it does not explicitly state whether the operation is read-only, nor does it cover rate limits, error handling, or pagination, leaving some behavioral gaps.

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

Conciseness4/5

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

The description is efficiently structured with a summary, an args list, and an alternative note. It front-loads the purpose and then details parameters. Slightly verbose with the API key instruction, but each sentence serves a purpose.

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?

Given 5 parameters and no output schema, the description covers purpose, filters, limits, and prerequisites. It could mention the return format (e.g., JSON) and potential error scenarios, but the essentials are present.

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

Parameters5/5

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

Schema description coverage is 0%, so the description is the only source of parameter meaning. It explains each parameter: state as a 2-letter code, company as partial match, days with max 730, limit with max 500, and api_key with tier requirement. This fully compensates for the schema's lack of descriptions.

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 clearly states 'Export WARN records in bulk' with a specific verb and resource. It distinguishes itself from sibling tools like search_layoffs (search) and get_recent_layoffs (recent data) by focusing on bulk export with full field details.

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

Usage Guidelines5/5

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

It explicitly directs users to the REST API for CSV/Parquet downloads, indicating when not to use this tool. It also states the Pro tier requirement upfront, giving clear prerequisites and an alternative path.

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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