WARN Firehose

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 warnfirehose.com/account

Args:
    api_key: Your WARN Firehose 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

Name	Required	Description	Default
`days`	No
`limit`	No
`state`	No
`api_key`	Yes
`company`	No

TDQS

A4.5/5.0

Behavior4/5

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

No annotations are provided, so the description takes on the full burden. It discloses the Pro tier requirement, API key necessity, maximum return size (500), and a boundary (no CSV/Parquet export, use REST API). While it lacks error handling or detailed return format, it covers key behavioral constraints.

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?

The description is well-structured with a lead sentence for purpose, followed by usage constraints and alternative, then a clean Args list. Every sentence adds value, and it is appropriately sized for 5 parameters.

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 purpose, authentication, limits, and a key alternative. With no output schema, it mentions 'full field details' but could be more specific about the return format or behavior when no records match. Still, it is reasonably complete for a bulk export tool with moderate complexity.

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 coverage is 0%, and the description fully compensates by explaining each of the 5 parameters: api_key (Pro tier), state (2-letter code), company (partial match), days (lookback range), and limit (max value). This adds significant meaning beyond the bare schema.

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 states a specific verb and resource: 'Export WARN records in bulk.' This clearly distinguishes the tool from siblings like search_layoffs or get_recent_layoffs by emphasizing bulk export capability.

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?

The description gives explicit usage context: requires Pro tier, returns up to 500 records, and directs users to the REST API for CSV/Parquet downloads as an alternative. It does not explicitly contrast with sibling functions, but the alternative is clearly stated.

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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TDQS

A3.9/5.0

Disambiguation3/5

Several tools have overlapping scopes: get_company_layoffs vs search_layoffs (company search), get_state_summary vs get_state_intelligence (state-level view), and get_market_pulse vs get_stats (overall statistics). While descriptions clarify some differences, an agent could easily misselect between these pairs.

Naming Consistency5/5

All tool names follow a verb_noun snake_case pattern, with the majority starting with 'get_' and the rest being clear single verbs (export_records, search_layoffs, authenticate). The naming is consistent and predictable.

Tool Count5/5

12 tools is well within the ideal 3-15 range. Each tool serves a discrete purpose (auth, export, queries, analytics, pricing, stats), and the count feels appropriate for a comprehensive data API.

Completeness4/5

The tool set covers querying WARN data by various dimensions, bulk export, cross-dataset analytics, and meta operations. Minor gaps include direct access to individual non-WARN datasets and a tool to fetch a single layoff notice by ID, but these are workarounds via search or export.

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