Schema library jobs

Return a job-posting record from a public page.

Pass this JSON Schema and a public source URL to/extract/json. Return title, employer, location, description, compensation, and application details present on the page.

Use this schema The JSON file

tabstack.ai/pricing

TEXT

MARKDOWN

LINKS

extract.tsTypeScript

const res = await client.extract.json({
  url: 'https://example.com/pricing',
  json_schema: {
    type: 'object',
    properties: {
      plan: { type: 'string' },
      price: { type: 'number' },
    },
  },
})

res = client.extract.json(
    url='https://example.com/pricing',
    json_schema={
        'type': 'object',
        'properties': {
            'plan': {'type': 'string'},
            'price': {'type': 'number'},
        },
    },
)

tabstack extract json https://example.com/pricing \
  --schema '{"type":"object","properties":{"plan":{"type":"string"},"price":{"type":"number"}}}'

What it captures

Fields in this job-posting record.

Schema for individual job listings extracted from job boards and company career pages.

Field	Type	What it holds
`title`	string, required	Job title or position name.
`company_name`	string, required	Name of the hiring company.
`company_domain`	string	Website domain of the hiring company.
`location`	string, required	Job location (city, state, country or Remote).
`remote_type`	string	Remote work type for this position.
`employment_type`	string	Employment type or contract duration.
`seniority_level`	string	Seniority level of the position.
`salary_min`	number	Minimum salary offered.
`salary_max`	number	Maximum salary offered.
`salary_currency`	string	ISO 4217 currency code for salary values.
`salary_interval`	string	Pay interval for salary figures.
`equity`	boolean	Whether equity or stock options are offered.
`description`	string, required	Full text of the job description.
`requirements`	array	List of job requirements or qualifications.
`tech_stack`	array	List of technologies, tools, or programming languages mentioned.
`benefits`	array	List of benefits offered.
`apply_url`	string, required	Direct URL to apply for the position.
`posted_date`	string	Date the job was posted.
`expiry_date`	string	Date the job listing expires.
`job_id`	string	Platform or company internal job identifier.
`source_platform`	string	Platform where the job was found (e.g., LinkedIn, Indeed).
`department`	string	Department or team for this role.
`visa_sponsorship`	boolean	Whether visa sponsorship is available.
`page_title`	string	Title of the source page. Tabstack auto-fills this from page metadata when left empty.
`favicon`	string	Favicon URL of the source page. Tabstack auto-fills this from page metadata when left empty.

Example

Inspect and validate the response shape.

The example below is generated from the schema to demonstrate its structure. Edit the object or paste a real response to validate it in your browser.

What it checks

Pass or fail, and the first reason why.

Whether the text parses as JSON, whether the top level is an object, and whether each field the schema requires is present at the declared type. A null is allowed anywhere. Every key you ask for is present. A field the page does not state can come back null, empty, a placeholder number, or a guessed value. Validate values, not just keys.

Example data, not a live response.

Usage

Send the schema with your source URL.

The schema travels with the request rather than living on your account, so the same call can send a trimmed version for one page and the full one for another. Every key you ask for is present. A field the page does not state can come back null, empty, a placeholder number, or a guessed value. Validate values, not just keys.

job.tsTypeScript

import schema from './job-posting.json'

const res = await client.extract.json({
  url: 'https://example.com/pricing',
  json_schema: schema,
})

tabstack extract json 'https://example.com/pricing' \
  --schema @./job-posting.json

Adaptation

Make the schema match your application.

The schema is a starting point, not a guarantee that every source page contains every field. Three things are worth doing before you write one into your system, and the schema-authoring guide covers the rest.

Remove what you do not need

A shorter schema is a smaller response and fewer fields to handle.

Describe the ambiguous ones

A description tells Extract what to look for when a label could mean two things.

Validate before you store

Check the returned object against the schema rather than trusting it.

Related schemas

Other schemas in this category.

Same category: company hiring velocity.
Same category: executive leadership change.
Same category: layoff event.
The job rather than the object: the Extract API.