# Job Board Change Monitor — Greenhouse, Ashby & Lever (`gertner-data/job-board-changes`) Actor

Keep job boards current with new, updated and removed vacancies from Greenhouse, Ashby and Lever. Get normalized jobs, stable IDs, field-level before/after changes and source evidence. Launch price: $0.01/checked board plus start; all job rows included.

- **URL**: https://apify.com/gertner-data/job-board-changes.md
- **Developed by:** [Евгений Гертнер](https://apify.com/gertner-data) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 checked boards

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

## Job Board Change Monitor — Greenhouse, Ashby & Lever

Keep job listings current with **normalized vacancies and field-level change evidence** from Greenhouse, Ashby and Lever. Sync a specialist job board, refresh a hiring-research database or route changes into an AI-agent workflow.

- **Up to 10 boards** in one batch; up to 5,000 jobs per board.
- **Before/after values** for titles, locations, descriptions, workplace type and structured compensation.
- **Stable source IDs and content hashes** for repeatable database upserts.
- **Launch price: $0.01 per checked board**, with all job rows included, plus $0.001 run start.
- **Complete-scan protection** preserves a healthy baseline during interrupted source checks.

### First run

```json
{
  "boards": [{"ats": "lever", "board": "spotify"}],
  "maxJobsPerBoard": 1000,
  "includeUnchanged": true
}
```

Use the company slug from its public career URL:

| ATS | Public URL | Input |
| --- | --- | --- |
| Greenhouse | job-boards.greenhouse.io/stripe | `{"ats":"greenhouse","board":"stripe"}` |
| Lever | jobs.lever.co/spotify | `{"ats":"lever","board":"spotify"}` |
| Lever EU | jobs.eu.lever.co/your-company | `{"ats":"lever","board":"your-company","region":"eu"}` |
| Ashby | jobs.ashbyhq.com/your-company | `{"ats":"ashby","board":"your-company"}` |

### Get jobs and change evidence

Each dataset row includes `id`, `ats`, `board`, `title`, `location`, `departments`, `employmentType`, `workplaceType`, `compensation`, `descriptionText`, `jobUrl`, `applyUrl`, `contentHash`, `warnings` and `observedAt`.

The first run uses `change: current`. With a previous snapshot, rows are `added`, `changed`, `unchanged` or `removed`. Changed rows include field names and before/after values:

```json
{
  "id": "greenhouse:global:example:123",
  "change": "changed",
  "changedFields": ["title"],
  "fieldChanges": {"title": {"before": "Engineer", "after": "Senior Engineer"}},
  "sourceComplete": true
}
```

`contentHash` covers normalized comparison fields. Plain-text conversion and whitespace normalization filter formatting-only description changes. Native structured workplace and compensation values are preserved; unavailable values use `null`.

`SUMMARY` contains board completeness, counts, errors, usage and budget outcomes. `SNAPSHOT` is issued when every requested board completes within size and spending caps. Export JSON, JSONL, CSV or Excel; use JSON for nested change evidence.

### Automate repeatable synchronization

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
actor = client.actor("gertner-data/job-board-changes")
inputs = {"boards": [{"ats": "lever", "board": "spotify"}]}
first = actor.call(run_input=inputs)
store = client.key_value_store(first["defaultKeyValueStoreId"])
summary = store.get_record("SUMMARY")["value"]
if not summary["snapshotAvailable"]:
    raise RuntimeError("Inspect SUMMARY before advancing the baseline")
baseline = store.get_record("SNAPSHOT")["value"]
second = actor.call(run_input={
    **inputs, "previousSnapshot": baseline, "includeUnchanged": False
})
for job in client.dataset(second["defaultDatasetId"]).iterate_items():
    print(job["change"], job["id"], job["changedFields"])
```

Your backend, n8n or Make owns the baseline: schedule → load snapshot → run Actor → route changes → save the next complete snapshot. Keep the previous healthy snapshot during failures. Supply the same board list between comparisons; omit `previousSnapshot` to reset.

### Pricing

**Launch price: $0.001 run start + $0.01 per checked board**, platform usage included. All job rows and snapshot data for each checked board are included.

| Boards | Event price |
| --- | --- |
| 1 | $0.011 |
| 3 | $0.031 |
| 10 | $0.101 |

A valid empty board or partially read board with usable jobs counts as checked. A board without usable source data receives no board event. The start event applies independently. `includeUnchanged` controls output, not the board price. Set the maximum run charge to limit spending before the next board is fetched.

### API coverage and run settings

Reads public listed postings from the three ATS posting APIs, including Lever EU. Removal events mean a posting left a completely read source board. Partial boards retain structured diagnostics; complete snapshots keep subsequent comparisons reproducible.

1–10 boards, 5,000 jobs per board, 15 MB per response, 20 MB downloaded per board, 6 MB combined baseline, 100 KB job text and 12 MB comparison output per board. Split large boards into appropriate runs and inspect `SUMMARY` for capped results. Lever uses live pagination; repeat a complete observation for consequential removal decisions.

20-second requests, two bounded retries for network errors/429/5xx. Default 512 MB; recommended timeout 600 seconds. Logs exclude job descriptions and query secrets. Inputs and results use your Apify retention settings. Use permitted public sources and their data-use terms.

For `http_error` 404, check the board slug or ATS migration. For `max_jobs_reached`, adjust the job limit within run caps. For `snapshotAvailable: false`, retain the previous complete baseline. Report issues with the run ID and `SUMMARY` error codes.

Support: [Evgeny Gertner](https://t.me/evgertner).

# Actor input Schema

## `boards` (type: `array`):

1–10 objects: ats (greenhouse, ashby, lever), board (public slug), optional region (global or eu for Lever). Find the slug in the public careers URL.

## `maxJobsPerBoard` (type: `integer`):

A cap makes that board incomplete: removals and the next snapshot are withheld.

## `includeUnchanged` (type: `boolean`):

Disable for changes-only dataset. Every checked board is still billed; SNAPSHOT retains the complete inventory.

## `previousSnapshot` (type: `object`):

Optional intact complete SNAPSHOT from this Actor, with the same board list. Omit for a baseline. No shared hidden state.

## Actor input object example

```json
{
  "boards": [
    {
      "ats": "lever",
      "board": "spotify"
    }
  ],
  "maxJobsPerBoard": 1000,
  "includeUnchanged": true
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

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

No description

## `snapshot` (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 = {
    "boards": [
        {
            "ats": "lever",
            "board": "spotify"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("gertner-data/job-board-changes").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 = { "boards": [{
            "ats": "lever",
            "board": "spotify",
        }] }

# Run the Actor and wait for it to finish
run = client.actor("gertner-data/job-board-changes").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 '{
  "boards": [
    {
      "ats": "lever",
      "board": "spotify"
    }
  ]
}' |
apify call gertner-data/job-board-changes --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gertner-data/job-board-changes"
        }
    }
}
```

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/jLX13tzm2T0qGkHjV/builds/oPNxJCwC9y1SecTSJ/openapi.json