Extract structured requirements from job descriptions using rule-based parsing.
npx skills add https://github.com/gw-ai-security/ats-cv-scorer --skill jd-parsing
Please help me install this Agent Skill. Skill: jd-parsing Source: https://github.com/gw-ai-security/ats-cv-scorer/tree/main/.codex/skills/jd-parsing Command: npx skills add https://github.com/gw-ai-security/ats-cv-scorer --skill jd-parsing
Diese Fähigkeit extrahiert aus Job Descriptions strukturierte Anforderungen, um Matching und Analyse effizienter zu gestalten.
Gib eine JD-Datei ein und lass das System die Felder extrahieren.
High-intent search queries and answers about installing and using this skill.
You extract structured requirements from job descriptions by inputting a JD file into the system. A rule-based parsing workflow then isolates standard fields like skills, experience, location, and work model.
Yes, you can parse German and English job descriptions. The system supports DE/EN JD variants and allows extensions to header recognition and parsing rules for both languages.
You can extract common job description fields such as requirements, skills, experience, location, and work model. These standardized outputs enable automated matching and analysis of large JD volumes.
You extend parsing rules for new job description fields by updating the core parser module and its associated unit tests. This rule-based workflow ensures new extraction logic remains reliable.
The best way to standardize large volumes of job postings is using a rule-based extraction workflow. It converts raw JD text into structured fields, enabling efficient automated recruitment processes.
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Sake-TeamRoutes structured text parsing decisions between regex and LLM validation.
