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Agent Data API

company_jobs

Open jobs at a company, from its own applicant tracking system's public job board: Greenhouse, Lever, Ashby, Workable, SmartRecruiters, Recruitee, BambooHR, Personio, Teamtailor, or Workday from a careers URL. Give a company name, website or job-board URL, with optional title, location and remote filters. Returns the newest 50 matching jobs with title, department, location, remote flag, salary when published, posting date and apply link, plus total counts. Costs $0.005 USDC on Base via x402.

Input Schema

NameRequiredDescriptionDefault
titleNoKeep jobs whose title contains this text; comma-separate alternatives (engineer,developer)
remoteNotrue keeps only jobs marked remote
companyYesCompany name (stripe), website (stripe.com) or job-board URL (https://jobs.lever.co/palantir)
locationNoKeep jobs whose location, country or workplace type contains this text (london, remote)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, this description carries the full load and does it well: it discloses the 50-result cap and 'newest first' ordering, the returned fields, total counts, and the $0.005 USDC-on-Base x402 cost. It stops short of describing failure behavior (company not found, unsupported ATS) or whether results can be paged beyond 50.

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?

Four sentences, front-loaded with purpose and source, then inputs, then return shape and cost. No filler, though the long ATS enumeration is dense and could be trimmed without losing meaning.

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

Completeness5/5

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

No output schema and no annotations, yet the description covers inputs, providers, result cap, returned fields, total counts and pricing. An agent has everything needed to decide to call it and to interpret the response.

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 description coverage is 100%, so the schema already documents company formats, comma-separated title alternatives, location matching, and the remote enum. The description restates those filters at a high level without adding syntax or edge-case semantics, so the baseline 3 applies.

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?

States a specific verb and resource ('Open jobs at a company') plus the exact data source (the company's own ATS public job board) and enumerates the supported providers. No sibling tool covers job listings, and the description makes the scope unmistakable on its own.

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?

Explicit invocation guidance: 'Give a company name, website or job-board URL, with optional title, location and remote filters.' Context is clear, but there are no when-not-to-use notes or fallback guidance if the company's board can't be detected.

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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