WARN Firehose

get_risk_signal

Get companies ranked by composite distress signal across all datasets.

Combines WARN layoff volume/recency, SEC restructuring filings,
bankruptcy filings, and H-1B denial rates into a single risk score.
Levels: Critical (7+), Elevated (4-6), Moderate (2-3), Low (1).
Requires Starter tier or higher. Get your API key at warnfirehose.com/account

Args:
    state: Optional 2-letter state code to filter
    min_score: Minimum risk score (default 3)
    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
`limit`	No
`state`	No
`api_key`	No
`min_score`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the composite signal construction, score levels (Critical, Elevated, Moderate, Low), and the authentication requirement. It doesn't mention rate limits or error behavior, but the core behavior and prerequisites are transparent.

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 front-loaded with the purpose, followed by a compact explanation of data sources and risk levels, then a structured Args list. Each sentence adds necessary information without wasted words, though it is slightly longer than strictly necessary.

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 the presence of an output schema and the description covering data sources, scoring levels, authentication, and parameter semantics, the tool is sufficiently described for correct selection and invocation. Explicit comparisons with sibling tools would enhance completeness but are not essential.

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. The Args section defines each parameter: state as a 2-letter code, min_score as the minimum threshold, limit with max 50, and api_key tied to the Starter tier. This fully compensates for the lack of schema 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 the tool returns companies ranked by a composite distress signal, combining WARN layoffs, SEC restructuring, bankruptcy filings, and H-1B denial rates. This distinguishes it from sibling tools like get_company_layoffs or get_state_intelligence by highlighting its cross-dataset risk-scoring focus.

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 implies usage as a broad risk screening tool across multiple datasets, with clear context that it is not a raw data query. It mentions the Starter tier requirement but does not explicitly name alternatives or provide when-not-to-use guidance. The tier prerequisite adds practical usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All WARN Firehose tools Inspect

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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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