Automate partial credit grading of handwritten math work on MyOpenMath.
npx skills add https://github.com/shuff57/agent-evo --skill grade-show-work
Please help me install this Agent Skill. Skill: grade-show-work Source: https://github.com/shuff57/agent-evo/tree/main/skills/.archive/grade-show-work Command: npx skills add https://github.com/shuff57/agent-evo --skill grade-show-work
This Skill automates the process of grading students' math work displayed on MyOpenMath pages, especially when partial credit is required for 'show your work' problems, saving teachers time and ensuring accurate evaluations.
Run the 'grade-show-work' skill with the MyOpenMath grading page URL to automatically evaluate student work and generate a report for teacher review.
High-intent search queries and answers about installing and using this skill.
You can automate grading 'show your work' math problems on MyOpenMath by running this Skill with the grading page URL. It uses image analysis to evaluate uploaded handwritten work and generates a partial credit report for teacher review.
Yes, automated partial credit grading requires the Playwright browser automation library to access MyOpenMath pages. It also depends on OpenCV and NumPy to perform image analysis on the student's uploaded work.
Yes, you can customize partial credit scoring criteria for student math assignments. The Skill adapts to various levels of demonstrated effort, automatically awarding customized point values like +2, +1, or +0 based on the visible work shown.
Automated math grading ensures a secure and compliant workflow by generating evaluation reports for teacher approval. No scores are changed automatically without teacher review, keeping the grading process secure.
Image analysis for grading handwritten math work uses OpenCV and NumPy to process uploaded images. The system evaluates the visible effort demonstrated in the work and applies custom scoring logic to award appropriate partial credit.
A key limitation of using image analysis to grade math work is that the automated evaluation requires teacher review before any scores are changed. The system assesses visible effort but relies on human approval to ensure accurate final scoring.
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