# JobPosting Markup Audit — Remote & Location Checks (`natstandridge/jobposting-markup-audit`) Actor

Audit public job-detail pages for JobPosting JSON-LD errors, remote-work geography, physical locations, dates and noindex signals. Get one precise report per page.

- **URL**: https://apify.com/natstandridge/jobposting-markup-audit.md
- **Developed by:** [Nathaniel Standridge](https://apify.com/natstandridge) (community)
- **Categories:** Jobs
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 inspected job pages

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## JobPosting Markup Audit

A job page can look fine to applicants while its structured data quietly loses a location, an employer name, or an indexable page. This Actor checks a list of public job-detail URLs and gives you a compact, repeatable report for each one.

It reads the **static HTML response** and inspects `JobPosting` JSON-LD. Findings point to a specific field, explain the problem in plain language, and suggest the next edit. A page that could not be fetched is reported as a fetch error, never as a clean page.

### Start with two pages

```json
{
  "urls": [
    "https://jobs.ashbyhq.com/openai/7613aca3-9dd8-41cd-b114-06ef4de967a9/",
    "https://example.com/"
  ],
  "maxRunSeconds": 120
}
```

The first URL is a public job-detail page that carried static JobPosting markup when this example was prepared; job pages can close or change. The second is a deliberate no-markup comparison. Replace both with your own public job URLs for production checks. The same input can be saved as an Apify Task and scheduled after career-site deployments.

**One dataset row per inspected URL.** `markupStatus` is `found` or `missing`. Open the **Findings** table for stable codes, severity, field path, and a concrete fix. URLs blocked by robots, timeouts, HTTP failures and non-HTML responses appear in `OUTPUT.fetchErrorDetails` with a stable code and time; they never appear as clean pages or billable dataset rows. `OUTPUT` also counts inspected pages, missing markup and pages with findings, and marks partial runs. Keep that summary beside exported data so a short run is not mistaken for a full audit.

Typical findings include `MISSING_DATEPOSTED`, `MISSING_HIRING_ORGANIZATION`, `MISSING_ADDRESS_COUNTRY`, `MISSING_REMOTE_GEOGRAPHY`, `MULTIPLE_JOBPOSTING`, `NOINDEX`, and `PAST_VALID_THROUGH`. A past `validThrough` is **informational**: Google documents it as a way to expire a closed job. A missing `validThrough` is not automatically a defect; it is required only if the posting has a known expiration.

### What is checked

| Area | Check |
| --- | --- |
| Page | HTTPS fetch, redirects, HTML content type, robots permissions, `noindex`, canonical link |
| JSON-LD | Parseable `JobPosting` in scripts and `@graph`; more than one job object on a detail page |
| Core fields | Job title, full description, original posting date, hiring organization name |
| Geography | Country on **every** physical `jobLocation`; `TELECOMMUTE` and eligible applicant locations for remote work |
| Dates | ISO 8601 syntax, future `datePosted`, and a published expiration earlier than the posting date |
| Optional fields | Documented employment-type and base-salary structure when those fields are present |

The code does not guess whether a job is really remote, whether a salary matches the visible page, or whether an employer is authorized to post. Those require human review. It does not claim that Google has crawled, indexed, or approved a page.

Linked fields using `@id` are resolved only when an exact matching node appears in the same JSON-LD block. Resolution is bounded to 1,000 nodes and expansions; missing, conflicting or cyclic references receive an explicit inspection finding. External references and remote JSON-LD contexts are never fetched. Date comparisons retain timestamp offsets and precision; when the supplied values lack enough timezone or time-of-day information for an unambiguous comparison, the report says so.

### Price and limits

The Store price is **$0.002 per successfully fetched and inspected page** ($2 per 1,000). A readable page with missing or broken markup still received an audit and is billable. Invalid input, duplicate URLs, robots blocks, HTTP failures, timeouts and non-HTML responses are not charged by this Actor. Apify's default dataset item event is the only charging path. Set a maximum total charge on the run if you need a hard cap. The `OUTPUT` record tells you when that cap stopped the batch.

Equivalent URLs with an explicit `:443` port are deduplicated, and international paths are encoded before fetching. If an interrupted output write has an unknown result, the run stops with an explicit `OUTPUT.stopReason`. A resumed run continues only after the saved dataset confirms that pending page; it does not send the same uncertain billable write again.

- 1–50 unique public HTTPS URLs per run; standard port 443 only.
- Static response only: no browser, JavaScript execution, login, proxy, or CAPTCHA handling. If markup is injected by JavaScript, this Actor reports it as absent from static HTML.
- Each page response is capped at 2 MB, each robots file at 256 KB, redirects at three, and each page's fetch work at 25 seconds including DNS, robots, redirects and body reads. Blocked fetch work is terminated at that deadline. The overall work budget is 30–180 seconds; bounded storage and summary operations can add shutdown time.
- Public DNS addresses are resolved and checked before every connection. The connection is pinned to the checked public IP, including after redirects. URL credentials and private or local destinations are rejected.
- At most 100 JSON-LD blocks and 20 JobPosting objects are checked per page; limit findings are explicit.
- Reports contain at most 100 findings. `FINDINGS_LIMIT` marks omitted findings; severity counts describe the findings displayed in the report.
- No application forms, applicant data or linked pages are fetched. The Actor stores only its dataset and run summary in your Apify account.

### Reading the result honestly

The findings are technical checks based on the [Google Search Central JobPosting guide](https://developers.google.com/search/docs/appearance/structured-data/job-posting), checked in November 2026. Google may change its rules. Use Google's [Rich Results Test](https://search.google.com/test/rich-results) and Search Console URL Inspection for the final view of a page. In particular, a syntactically correct object can still describe a closed, misleading, or inaccessible job; automated markup checks cannot settle that.

For a reproducible problem, open an issue on this Actor's Apify page with the run ID, public page URL, expected finding and observed finding. Do not include credentials, signed URLs or applicant information.

# Actor input Schema

## `urls` (type: `array`):

1–50 public HTTPS job-detail pages. Do not use listing pages, signed URLs, login-only pages or private hosts. Duplicate URLs are checked once.

## `maxRunSeconds` (type: `integer`):

The Actor stops starting new page checks after this many seconds and marks the run partial. Use a platform timeout at least 60 seconds longer.

## Actor input object example

```json
{
  "urls": [
    "https://jobs.ashbyhq.com/openai/7613aca3-9dd8-41cd-b114-06ef4de967a9/"
  ],
  "maxRunSeconds": 120
}
```

# Actor output Schema

## `audits` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "urls": [
        "https://jobs.ashbyhq.com/openai/7613aca3-9dd8-41cd-b114-06ef4de967a9/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("natstandridge/jobposting-markup-audit").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "urls": ["https://jobs.ashbyhq.com/openai/7613aca3-9dd8-41cd-b114-06ef4de967a9/"] }

# Run the Actor and wait for it to finish
run = client.actor("natstandridge/jobposting-markup-audit").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "urls": [
    "https://jobs.ashbyhq.com/openai/7613aca3-9dd8-41cd-b114-06ef4de967a9/"
  ]
}' |
apify call natstandridge/jobposting-markup-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,natstandridge/jobposting-markup-audit"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Hm5eZyRJhyEu9SWOz/builds/qzg7ZYfGQ03d666vc/openapi.json