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datasets_jobs_search

Search live job postings from multiple ATS platforms with full-text and faceted filters. Find open roles by company, location, department, and more.

Instructions

Search the jobs dataset (all companies' live postings). Full-text + faceted search over every job posting crawled from every discovered company ATS board (Greenhouse, Lever, Ashby, Workday, SmartRecruiters, Workable, Recruitee, Rippling, Personio, Teamtailor, Oracle, UKG). Open roles only by default (set include_closed=true for historical/filled roles). provider enum: greenhouse, lever, ashby, workday, smartrecruiters, workable, recruitee, rippling, personio, teamtailor, oracle, ukg. sort enum: relevance, posted_desc, company_asc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text over title, company, description
pageNoPage number, default 1
sortNoSort enum: relevance, posted_desc, company_asc
remoteNoFilter by remote (true or false)
companyNoCompany name match
locationNoLocation match
providerNoATS provider filter. Enum: greenhouse, lever, ashby, workday, smartrecruiters, workable, recruitee, rippling, personio, teamtailor, oracle, ukg
page_sizeNoPage size, default 20, max 100; page*page_size must be <= 10000
departmentNoExact department filter
include_closedNoInclude closed/filled roles (default false = open only)
employment_typeNoExact employment-type filter
Behavior3/5

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

With no annotations, the description carries full burden. It covers search scope (all companies, live postings) and default open roles, but lacks details on data freshness, rate limits, pagination limits (only implied via schema), or result completeness.

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 a concise three-sentence paragraph, front-loaded with purpose. It could be better structured (e.g., bullet points), but efficiently covers key points without waste.

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

Completeness2/5

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

Given 11 parameters and no output schema, the description only highlights include_closed and sort, but omits other facets (remote, company, location, department, employment_type). No hint about response structure or advanced usage, making it incomplete for a complex search tool.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds minimal extra value beyond schema, mainly reiterating provider and sort enum values and default behaviors already in 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 specifies the verb 'search', the resource 'jobs dataset (all companies' live postings)', and provides details on ATS providers and sort options. It effectively distinguishes from other job tools like datasets_jobs_item and datasets_jobs_facets.

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 clear context for the default behavior (open roles only) and when to use include_closed, but does not compare with sibling jobs tools (e.g., datasets_jobs_nearby) or state explicit alternatives.

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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