Multilingual Skills Extraction API

API ID 13176

Extract normalized professional skills from text in any language. Works where English-only parsers fail: catches implicit soft skills and returns clean, structured JSON with confidence scores.

API Documentation

Endpoints

Request

Takes raw text (a job posting or a resume) and returns a list of normalized professional skills, each with a standard
ESCO-style label, a hard or soft type, and a confidence score. Works in any language.

Endpoint ID: 26723
POST https://zylalabs.com/api/13176/multilingual+skills+extraction+api/26723/parse+skills
INPUT PARAMETERS

Parse Skills — Endpoint Features

Object Description
text Required The raw text to extract skills from (a job posting or a resume), in any language.

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

text
API EXAMPLE RESPONSE
JSON
{"skills":[{"name":"Leadership","esco_label":"leadership","type":"soft","confidence":0.95},{"name":"Mentoring","esco_label":"mentoring","type":"soft","confidence":0.95}]}
Parse Skills — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/13176/multilingual+skills+extraction+api/26723/parse+skills?text=led the team and mentored 3 juniors' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Multilingual Skills Extraction API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

Simple Transparent Pricing

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Minimum annual contract: USD 10,000

Trusted by leading companies

Overview

Skills Extraction API turns any job posting or resume into a clean, structured list of professional skills, in any language.

Unlike keyword-based parsers, it uses an LLM to understand context, so it catches IMPLICIT soft skills ("led the team"
becomes Leadership, "mentored juniors" becomes Mentoring) and works on non-English text (Korean, Spanish, Japanese, etc.)
where simpler parsers return an empty result.

For each skill you get:
- name: canonical, searchable name (for example "js" becomes "JavaScript", "k8s" becomes "Kubernetes")
- esco_label: standard ESCO/O*NET-style label
- type: "hard" or "soft"
- confidence: a 0 to 1 score

One endpoint: POST /parse-skills with { "text": "..." } returns { "skills": [...] }

Built for ATS enrichment, job-candidate matching, resume parsing, talent analytics, and recruiting automation. No
preprocessing and no model setup: paste raw text, get normalized JSON back.

Multilingual Skills Extraction API FAQs

The API extracts both hard and soft skills from text, including implicit soft skills such as leadership and mentoring, by understanding the context in which they are mentioned.

The API returns a clean, structured JSON format that includes fields such as 'name' (canonical name), 'esco_label' (standard label), 'type' (hard or soft), and 'confidence' (a score from 0 to 1).

The API can be used for ATS enrichment, job-candidate matching, resume parsing, talent analytics, and recruiting automation, making it valuable for HR and recruitment professionals.

The core value proposition lies in its ability to provide accurate, normalized skill extraction from diverse text inputs, enhancing recruitment processes and improving talent matching through structured data.

Any language the underlying LLM understands, which covers most major world languages. Skill names are always normalized to canonical English.

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