Which languages are supported for CV extraction?

The skill is specifically designed to handle and test both German (DE) and English (EN) resumes.

Which files does this skill help maintain?

It focuses on updating the core extraction logic in Python files and managing corresponding unit tests for quality assurance.

How does it handle missing information in a CV?

It follows a strict protocol to mark any missing mandatory fields as 'not found' rather than making assumptions, ensuring data integrity.

Does this skill use LLMs for extraction?

While the skill is used within Claude, it prioritizes rule-based extraction logic to ensure that results are auditable and not 'black-box' models.

ATS Criteria Extraction

Name: ATS Criteria Extraction
Author: gw-ai-security

bygw-ai-security

数据科学与机器学习

Extracts structured recruitment data from CVs for automated processing and ATS integration.

关于

The ATS Criteria Extraction skill provides a standardized approach for pulling essential information from resumes, including contact details, professional experience, and education. Unlike purely probabilistic models, this skill emphasizes rule-based extraction to ensure that recruitment decisions remain transparent, auditable, and explainable. It is ideal for developers building or maintaining Applicant Tracking Systems (ATS) who need to refine extraction logic, add new data fields, or ensure robust error handling for incomplete candidate profiles across both German and English languages.

主要功能

Automated extraction of contact, education, and experience data
Integrated unit testing for extraction validation
Support for multilingual processing (German and English)
Standardized flagging of missing fields as 'not found'
0 GitHub stars
Rule-based logic for transparent and auditable results

使用场景

Updating recruitment criteria rules in an existing ATS
Building automated CV screening pipelines with high explainability
Implementing auditable data extraction for compliance-heavy hiring

关于

主要功能

Automated extraction of contact, education, and experience data
Integrated unit testing for extraction validation
Support for multilingual processing (German and English)
Standardized flagging of missing fields as 'not found'
0 GitHub stars
Rule-based logic for transparent and auditable results

使用场景

Updating recruitment criteria rules in an existing ATS
Building automated CV screening pipelines with high explainability
Implementing auditable data extraction for compliance-heavy hiring