{"skills":[{"name":"Leadership","esco_label":"leadership","type":"soft","confidence":0.95},{"name":"Mentoring","esco_label":"mentoring","type":"soft","confidence":0.95}]}
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'
Después de registrarte, a cada desarrollador se le asigna una clave de acceso a la API personal, una combinación única de letras y dígitos proporcionada para acceder a nuestro endpoint de la API. Para autenticarte con el Multilingual Skills Extraction API simplemente incluye tu token de portador en el encabezado de Autorización.
| Encabezado | Descripción |
|---|---|
Autorización
|
Requerido
Debería ser Bearer access_key. Consulta "Tu Clave de Acceso a la API" arriba cuando estés suscrito.
|
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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.
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.