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APVentureEngine

warn-mcp

by APVentureEngine
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_layoff_notices

Find US WARN Act mass-layoff notices filed since 1988 by employer, state, date range, or minimum headcount. Returns matching notices with worker counts and dates, newest first.

Instructions

Search US WARN Act mass-layoff notices across 48 states, 1988 to today, by employer name, state, date range and minimum headcount (filters combine with AND; at least one is required). Returns matched_notices, matched_workers_affected and up to limit notices, newest notice_date first, each with id, state, company, location, employees_affected, notice_date, effective_date, notice_type and first_seen. Read-only, no key. For only the newest ~14 days use latest_layoff_notices; for one employer's whole record use employer_layoff_history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax notices returned, 1-200 (default 25).
sinceNoEarliest notice_date, YYYY-MM-DD.
stateNoTwo-letter state code, e.g. 'CA'.
untilNoLatest notice_date, YYYY-MM-DD.
companyNoEmployer name, matched on WHOLE WORDS (case-insensitive), e.g. 'united airlines'. Every word you give must appear as a complete word in the filed name, so 'ford' will NOT return 'Stanford Health Care'. On 0 hits the response lists similar_company_names to retry with.
min_employeesNoOnly notices affecting at least this many workers.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.4
    • changedInput schema / properties / company / description
      Previous value: -"Case-insensitive substring of the employer name, e.g. 'united airlines'."New value: +"Employer name, matched on WHOLE WORDS (case-insensitive), e.g. 'united airlines'. Every word you give must appear as a complete word in the filed name, so 'ford' will NOT return 'Stanford Health Care'. On 0 hits the response lists similar_company_names to retry with."
  2. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full transparency burden. It discloses read-only behavior, no API key needed, filter combination semantics, mandatory filter requirement, sort order (newest notice_date first), and the exact response contract including matched counts and per-notice fields.

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?

Every sentence earns its place: scope and filters, response format, safety/access traits, and sibling routing. Dense but not bloated, with the most decision-relevant information front-loaded.

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

Completeness5/5

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

Given six optional parameters and no output schema, the description fully compensates by specifying the return shape, sorting, count semantics, and read-only nature. Nothing an agent needs to invoke or interpret results correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents each parameter. The description adds valuable cross-parameter semantics: filters combine with AND, at least one is required, and limit caps returned notices. This goes beyond what individual parameter descriptions provide.

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?

States a specific verb (Search), precise resource (US WARN Act mass-layoff notices), scope (48 states, 1988–today), and the available filter dimensions. It also differentiates from siblings by explicitly naming latest_layoff_notices and employer_layoff_history as alternatives.

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?

Provides explicit routing guidance: 'For only the newest ~14 days use latest_layoff_notices; for one employer's whole record use employer_layoff_history.' It also states when to use this tool via filter requirements: at least one filter is required and filters combine with AND.

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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