Automation scripts for deploying and marking WorldSkills Competition 2017 Skill 39 Module C test projects using Ansible and pyATS testing frameworks.
git clone https://github.com/menus12/skill39-wsc2017-mod-c.gitThis skill provides deployment and marking automation for the WorldSkills International Competition 2017 Skill 39 Module C test project. It includes Ansible playbooks for automated test project deployment across network devices and pyATS testing scripts for automated marking and validation. The test project covers comprehensive networking configuration tasks including switching, routing, services, security, monitoring, backup, and WAN/VPN technologies aligned with Cisco certification standards. Organizations preparing for or administering WorldSkills competitions can use these scripts to streamline test environment setup and assessment processes.
Deploy test projects using the Ansible playbooks in the ./deployment/ directory. Run pyATS testing scripts from ./testing/ to automatically mark and validate completed configurations. Reference the provided initial configs and completed examples in ./configs/ for deployment guidance.
Automated deployment of WSC 2017 Skill 39 network test environments
Automated marking and validation of student network configurations
Consistent test project setup across multiple competition sites
Network skills assessment in educational and competition settings
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/menus12/skill39-wsc2017-mod-cCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Automate the grading process for [COMPANY]'s [INDUSTRY] training program using the WSC 2017 Skill 39 Module C scripts. The program has [NUMBER] of participants and [NUMBER] of assessments. Provide a step-by-step guide to implement the automation, including data preparation, script execution, and result analysis.
## Automated Grading Process for [COMPANY]'s [INDUSTRY] Training Program ### Step 1: Data Preparation - Gather all assessment data in a structured format (e.g., CSV or Excel). - Ensure data includes participant IDs, assessment scores, and any additional metadata. - Clean the data to remove any duplicates or inconsistencies. ### Step 2: Script Execution - Clone the WSC 2017 Skill 39 Module C repository from GitHub. - Install any necessary dependencies listed in the repository's README file. - Run the automation scripts using the command line, specifying the path to your data file. ### Step 3: Result Analysis - The scripts will generate a summary report with the following information: - Total number of participants graded. - Average score across all assessments. - Distribution of scores (e.g., number of participants scoring above 80%, etc.). - Review the report to identify any outliers or areas for improvement in the training program. ### Step 4: Integration with Existing Systems - Export the graded data to your preferred format (e.g., CSV, Excel, or database). - Integrate the graded data with your existing learning management system (LMS) or HR platform. - Set up automated notifications to inform participants of their grades and provide feedback.
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