WARN Firehose

get_talent_pipeline

Find available talent from recent layoffs, cross-referenced with LCA visa roles.

Shows what occupations/skills each laid-off company was hiring for.
Useful for recruiters targeting skilled workers from recently laid-off companies.
Requires Starter tier or higher. Get your API key at warnfirehose.com/account

Args:
    state: Optional 2-letter state code
    days: Look back this many days (default 90)
    limit: Max results (default 15, max 50)
    api_key: Your WARN Firehose API key (Starter tier required)

Input Schema

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It explains the data source (recent layoffs + LCA visa roles), the type of output (occupations/skills per company), and the authentication/API key requirement. It does not explicitly state read-only behavior, but 'Find' implies a safe read operation, and the description adds valuable access context beyond what structured fields provide.

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 appropriately sized and front-loaded. The purpose is stated in the first sentence, followed by a short clarification of output, a use-case sentence, and a structured Args list. Every sentence contributes value, and the list format improves scannability.

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 four optional parameters, an output schema, and a non-trivial cross-referencing behavior, the description covers purpose, usage, parameter details, and access requirements. It lacks explicit mention of return value structure, but the output schema is expected to fulfill that. The description is sufficiently complete for an agent to select and invoke it correctly.

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?

The input schema provides only types and defaults, with zero description coverage. The description's Args section fully explains each parameter: state (2-letter code, optional), days (lookback default 90), limit (max results default 15, max 50), and api_key (Starter tier required). This adds complete semantic meaning absent from the 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 opens with a specific verb 'Find' and a clear resource: 'available talent from recent layoffs, cross-referenced with LCA visa roles.' This distinguishes it from sibling tools like get_recent_layoffs or get_company_layoffs by focusing on talent discovery and the unique LCA cross-reference. The purpose is unambiguous.

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 states it is 'Useful for recruiters targeting skilled workers from recently laid-off companies,' which gives a clear use case. It also mentions the Starter tier requirement as a prerequisite. However, it does not explicitly name alternative tools or when not to use it, leaving some room for interpretation.

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.

Resources

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