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datasets_jobs_companies

Find which companies are hiring. Searches the discovered company board registry — which companies are hiring, on which ATS (or, for the 5 single-company big-tech providers, which platform), with how many open roles.

Instructions

Find which companies are hiring. Searches the discovered company board registry — which companies are hiring, on which ATS (or, for the 5 single-company big-tech providers, which platform), with how many open roles. Set sponsors_visa=true to keep companies with certified employer filings in recent public U.S. Department of Labor LCA disclosure data. This is company-level historical evidence, not a guarantee for a specific role or candidate. provider enum: greenhouse, lever, ashby, workday, smartrecruiters, workable, recruitee, rippling, personio, teamtailor, oracle, ukg, icims, eightfold, gem, pinpoint, amazon-jobs, apple-jobs, google-jobs, meta-jobs, tesla-jobs. status enum: active, empty, gone, blocked, pending, invalid. sort enum: open_desc, company_asc, crawled_desc. Billing: this endpoint costs 1 credit per 10 records returned, rounded up, with a minimum of 1 (up to 10 records cost 1, a full page of 100 costs 10).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoMatch on company name / domain
pageNoPage number, default 1
sortNoSort enum: open_desc, company_asc, crawled_desc
statusNoBoard status. Enum: active, empty, gone, blocked, pending, invalid
providerNoProvider filter
page_sizeNoPage size, default 20, max 100
sponsors_visaNoKeep companies with recent certified DOL LCA filings (default false)
min_open_rolesNoMinimum open roles

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.17.5
    • addedInput schema / properties / provider / enum
      Added value: +[
+  "greenhouse",
+  "lever",
+  "ashby",
+  "workday",
+  "smartrecruiters",
+  "workable",
+  "recruitee",
+  "rippling",
+  "personio",
+  "teamtailor",
+  "oracle",
+  "ukg",
+  "icims",
+  "eightfold",
+  "gem",
+  "pinpoint",
+  "amazon-jobs",
+  "apple-jobs",
+  "google-jobs",
+  "meta-jobs",
+  "tesla-jobs"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "open_desc",
+  "company_asc",
+  "crawled_desc"
+]
    • addedInput schema / properties / status / enum
      Added value: +[
+  "active",
+  "empty",
+  "gone",
+  "blocked",
+  "pending",
+  "invalid"
+]
  2. Changed3 schema fields changed
    • changedInput schema / properties / provider / description
      Previous value: -"ATS provider filter"New value: +"Provider filter"
    • addedInput schema / properties / sponsors_visa
      Added value: +{
+  "description": "Keep companies with recent certified DOL LCA filings (default false)",
+  "type": "boolean"
+}
    • changedInput schema / properties / status / description
      Previous value: -"Board status. Enum: active, empty, gone, blocked, pending"New value: +"Board status. Enum: active, empty, gone, blocked, pending, invalid"
  3. Addedv1.6.0

TDQS

A3.7/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden and does so reasonably: it discloses the data source (company board registry, DOL LCA filings), the cost model (1 credit per 10 records, rounded up, min 1, 100 records = 10 credits), and an important caveat that visa data is historical evidence rather than a guarantee. It stops short of stating auth requirements or rate limits.

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

Conciseness3/5

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

The core purpose is front-loaded in the first clause, which is good. But the description then re-lists the entire provider, status, and sort enums verbatim, which the input schema already enumerates at 100% coverage — that repeated block is largely wasted space and dilutes the otherwise tight prose.

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?

For an 8-parameter tool with no output schema and no annotations, the description supplies the key missing context: what the registry contains, the cost of a call, and the caveat on visa evidence. The main remaining gap is nothing about authorization or what a returned record looks like, but coverage is otherwise strong.

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 enum values for provider/status/sort are already fully documented and the baseline would be 3. The description exceeds that by explaining semantic meaning the schema lacks — notably what sponsors_visa actually filters on and the special handling of the 5 single-company big-tech providers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Find which companies are hiring') and scopes it precisely to the discovered company board registry, including the ATS/platform dimension and open-role counts. This inherently separates it from job-level siblings, but it never names a specific alternative such as datasets_jobs_search or jobs_company_search to fully differentiate.

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

Usage Guidelines3/5

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

Gives concrete usage guidance for one parameter ('Set sponsors_visa=true to keep companies with certified employer filings'), which tells the agent when to flip a flag. However, there is no when-to-use/when-not guidance relative to the many job and company-search siblings, so the agent must infer the choice itself.

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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