# Skills Normalizer - Map Free-Text Skills to a Taxonomy (`hirelayer/skills-normalizer`) Actor

Map free-text skills (a skills section, a job ad excerpt, a list) to a taxonomy of 11,000+ skills with stable IDs, types, families and domains.

- **URL**: https://apify.com/hirelayer/skills-normalizer.md
- **Developed by:** [HireLayer](https://apify.com/hirelayer) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $50.00 / 1,000 normalized texts

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

### What does Skills Normalizer do?

**Skills Normalizer** maps free-text skills to a taxonomy of **11,000+ skills**. Send a skill, a list or a whole skills section, and get for each skill found:

- a **stable ID** (`excel`, `react`…) to store and filter on,
- the **canonical name**, in the output language you choose,
- its **type**: hard skill, software, certification, soft skill or language,
- its **families** and **domains** (e.g. Frontend development → Software Development),
- a **broader** skill to widen a search (Excel → Microsoft Office),
- the **mention** in your text it was found in.

Parts of the text that match no skill are listed in `unresolved`, with likely families, so nothing is guessed.

It is powered by the [HireLayer](https://hirelayer.co) skills API. Processing runs in the EU.

### Why use it?

- **Clean skill data**: "MS Excel", "excel avancé" and "Microsoft Excel" become one skill.
- **Better search and matching**: filter candidates or jobs by skill ID, family or domain.
- **Labour market analytics**: count skills across job ads or profiles without spelling noise.

### How to use it

1. Click **Try for free**.
2. Enter one text per line (up to 5,000 characters each).
3. Choose the output language and click **Start**.

### Input

```json
{
  "texts": ["React, TypeScript, Node.js, AWS, Excel, project management, fluent Spanish"],
  "language": "en"
}
```

### Output

One dataset item per text:

```json
{
  "input_text": "React, TypeScript, Excel, fluent Spanish, project management",
  "status": "success",
  "language": "en",
  "skills": [
    {
      "id": "react",
      "name": "React",
      "type": "software",
      "mention": "React",
      "families": [{ "id": "frontend_development", "name": "Frontend development", "domain_id": "software_development" }],
      "domains": [{ "id": "software_development", "name": "Software Development" }],
      "broader": null
    }
  ],
  "unresolved": [],
  "taxonomy_version": "v1"
}
```

### Pricing

**$0.05 per text**, whatever the number of skills it contains. A text that cannot be processed is not charged.

### Use it from code

```bash
curl -X POST "https://api.apify.com/v2/acts/hirelayer~skills-normalizer/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"texts": ["Python, SQL, Power BI"], "language": "en"}'
```

The Actor is also available to AI agents through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp).

### FAQ

**Can I see the whole taxonomy?** Yes, through the [HireLayer Skills API](https://hirelayer.co/api-docs/skills).

**Need help?** Open an issue in the **Issues** tab or write to contact@hirelayer.co.

# Actor input Schema

## `texts` (type: `array`):

One text per line: a single skill, a list or a whole skills section (up to 5,000 characters each). Each text is one charged event.

## `language` (type: `string`):

Language of the skill, family and domain names returned.

## Actor input object example

```json
{
  "texts": [
    "React, TypeScript, Node.js, AWS, Excel, project management, fluent Spanish",
    "Google Sheet, Power BI, SQL, stakeholder management"
  ],
  "language": "en"
}
```

# Actor output Schema

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

One item per input text: resolved skills and unresolved parts.

# 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 = {
    "texts": [
        "React, TypeScript, Node.js, AWS, Excel, project management, fluent Spanish",
        "Google Sheet, Power BI, SQL, stakeholder management"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("hirelayer/skills-normalizer").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 = { "texts": [
        "React, TypeScript, Node.js, AWS, Excel, project management, fluent Spanish",
        "Google Sheet, Power BI, SQL, stakeholder management",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("hirelayer/skills-normalizer").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 '{
  "texts": [
    "React, TypeScript, Node.js, AWS, Excel, project management, fluent Spanish",
    "Google Sheet, Power BI, SQL, stakeholder management"
  ]
}' |
apify call hirelayer/skills-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hirelayer/skills-normalizer"
        }
    }
}
```

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/YKMgJ7nbOmhvj1fN3/builds/dq6pmZ5E83YeRqZx5/openapi.json