Does this skill help with objective grading?

Yes, it specializes in creating detailed grading rubrics (scoring matrices) that define specific evaluation dimensions and performance levels to ensure consistency.

Can I use this for non-coding related education?

Absolutely. While it's a Claude Code skill, its logic for assessment design, rubric creation, and data analysis applies to any subject or industry.

How does it analyze learning data?

The skill can process learning results to identify knowledge gaps, measure progress against objectives, and generate feedback reports for both instructors and learners.

What types of questions can the Learning Assessor generate?

It supports a wide variety of formats including multiple-choice, fill-in-the-blanks, short answers, and long essays, all with corresponding reference answers and difficulty levels.

Learning Assessor

Name: Learning Assessor
Author: partme-ai

bypartme-ai

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Learning & Documentation

Simplifies the creation of educational assessment tools, including quizzes, grading rubrics, and detailed learning analytics.

About

The Learning Assessor skill empowers educators and developers to build comprehensive educational frameworks directly within Claude Code. It streamlines the design of multi-format quizzes, establishes objective grading rubrics with weighted criteria, and provides tools for analyzing learner performance to identify specific knowledge gaps. Whether you are building an e-learning platform, internal developer onboarding programs, or automated testing suites, this skill ensures that assessments are pedagogically sound, aligned with learning objectives, and deliver actionable data for continuous performance improvement.

Key Features

Perform learning data analysis to identify trends, difficulties, and thin knowledge areas.
Create standardized peer-evaluation and self-assessment tools.
Design multi-format quiz questions (MCQ, short answer, essay) with difficulty leveling.
37 GitHub stars
Generate structured grading rubrics with clear evaluation dimensions and weights.
Generate personalized feedback reports and constructive improvement suggestions.

Use Cases

Developing automated onboarding assessments and technical tests for new developers.
Analyzing training data to produce personalized learning paths for enterprise education.
Creating structured rubrics for code reviews and project-based learning evaluations.

About

Key Features

Perform learning data analysis to identify trends, difficulties, and thin knowledge areas.
Create standardized peer-evaluation and self-assessment tools.
Design multi-format quiz questions (MCQ, short answer, essay) with difficulty leveling.
37 GitHub stars
Generate structured grading rubrics with clear evaluation dimensions and weights.
Generate personalized feedback reports and constructive improvement suggestions.

Use Cases

Developing automated onboarding assessments and technical tests for new developers.
Analyzing training data to produce personalized learning paths for enterprise education.
Creating structured rubrics for code reviews and project-based learning evaluations.