Schema library social-content

Return a software-review record from a public page.

Pass this JSON Schema and a public source URL to/extract/json. Normalize public review, rating, product, date, and source fields.

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 software-review record.

Software review from G2, Capterra, Trustpilot, etc.

Field	Type	What it holds
`platform`	string, required	The review platform where this review was published.
`product_name`	string, required	Name of the software product being reviewed.
`product_slug`	string	URL slug or identifier for the product on the review platform.
`product_url`	string	URL to the product listing on the review platform.
`reviewer_name`	string	Name or alias of the reviewer.
`reviewer_title`	string	Job title of the reviewer.
`reviewer_company_size`	string	Company size bracket of the reviewer's employer.
`reviewer_industry`	string	Industry of the reviewer's company.
`reviewer_verified`	boolean	Whether the reviewer identity has been verified by the platform.
`rating_overall`	number, required	Overall rating given by the reviewer, out of 5.
`rating_ease_of_use`	number	Ease-of-use rating out of 5.
`rating_features`	number	Features rating out of 5.
`rating_customer_support`	number	Customer support rating out of 5.
`rating_value_for_money`	number	Value-for-money rating out of 5.
`review_title`	string	Title or headline of the review.
`review_body`	string	Full text body of the review.
`pros`	string	Pros section of the review.
`cons`	string	Cons section of the review.
`use_case`	string	Described use case or problem the reviewer is solving.
`review_date`	string, required	Date the review was published (YYYY-MM-DD).
`helpful_count`	number	Number of users who marked this review as helpful.
`verified_purchase`	boolean	Whether the reviewer is a verified purchaser of the product.
`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.

software.tsTypeScript

import schema from './software-review.json'

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

tabstack extract json 'https://example.com/pricing' \
  --schema @./software-review.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: news article.
Same category: social profile.
The job rather than the object: the Extract API.