# HiringPilot — B2B Hiring Signal Lead Qualifier (`orbitai/hiring-signal-lead-qualifier`) Actor

Ranks company and job pages by hiring urgency, department growth, vendor need, and outreach angles for B2B sales teams.

- **URL**: https://apify.com/orbitai/hiring-signal-lead-qualifier.md
- **Developed by:** [Daniel Lozano](https://apify.com/orbitai) (community)
- **Categories:** Lead generation, Jobs, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $100.01 / 1,000 results

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/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## HiringPilot — B2B Hiring Signal Lead Qualifier

### What This Actor Does

Ranks company and job pages by hiring urgency, department growth, vendor need, and outreach angles for B2B sales teams.

### Who It Is For

- B2B sales teams
- recruiting agencies
- staffing agencies
- RevOps teams

### Why It Is Useful

Job scrapers extract listings; this translates hiring signals into vendor sales opportunities.

### Input Fields

- `startUrls`: public website URLs to process.
- `maxItems`: maximum URLs to process.
- `includeAiAnalysis`: optional AI enrichment when API keys are configured.
- `industryHint`: optional category hint.

### Example Input

```json
{
  "startUrls": [
    {
      "url": "https://example.com"
    }
  ],
  "maxItems": 1,
  "includeAiAnalysis": false,
  "industryHint": "local business"
}
```

### Example Output

```json
{
  "inputUrl": "https://example.com",
  "status": "success",
  "score": 64,
  "opportunityScore": 45,
  "findings": {},
  "missingItems": [],
  "recommendations": [],
  "createdAt": "2026-06-17T18:20:00.602Z"
}
```

### Output Schema

The Actor declares `.actor/output_schema.json` and links the `results` output to the default dataset items URL. This helps Apify Console, API consumers, and AI agents discover where run results are stored.

### Limitations

Public HTML only. No login-protected scraping, private APIs, legal compliance claims, or browser UI testing.

### Local Development

```bash
npm install
npm run build
npm test
npm run lint
apify run
```

### Deployment

```bash
apify push
```

# Actor input Schema

## `startUrls` (type: `array`):

Public website URLs to process.

## `maxItems` (type: `integer`):

Maximum URLs to process.

## `includeAiAnalysis` (type: `boolean`):

Use optional AI enrichment when keys are configured.

## `industryHint` (type: `string`):

Optional business category hint.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://example.com"
    }
  ],
  "maxItems": 25,
  "includeAiAnalysis": true,
  "industryHint": ""
}
```

# Actor output Schema

## `results` (type: `string`):

Default dataset items containing status, scores, findings, missing items, recommendations, and metadata for each processed URL.

# 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 = {
    "startUrls": [
        {
            "url": "https://example.com"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("orbitai/hiring-signal-lead-qualifier").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 = { "startUrls": [{ "url": "https://example.com" }] }

# Run the Actor and wait for it to finish
run = client.actor("orbitai/hiring-signal-lead-qualifier").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "startUrls": [
    {
      "url": "https://example.com"
    }
  ]
}' |
apify call orbitai/hiring-signal-lead-qualifier --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=orbitai/hiring-signal-lead-qualifier",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/nKM2YUQhSCM5pHLKe/builds/gAehRyyFMnAourxnp/openapi.json