Agent skill · Data & Analytics

scholar-evaluation

Systematic framework for evaluating scholarly and research work based on the ScholarEval methodology. This skill should be used when assessing research papers, evaluating literature reviews, scoring research methodologies, analyzing scientific writing quality, or applying structured evaluation criteria to academic work. Provides comprehensive assessment across multiple dimensions including problem formulation, literature review, methodology, data collection, analysis, results interpretation, and scholarly writing quality.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill scholar-evaluation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 10 KB
Bundled scripts: none
Path: skills/analysis/scholar-evaluation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Scholar Evaluation ## Overview Apply the ScholarEval framework to systematically evaluate scholarly and research work. This skill provides structured evaluation methodology based on peer-reviewed research assessment criteria, enabling comprehensive analysis of academic papers, research proposals, literature reviews, and scholarly writing across multiple quality dimensions. ## When to Use This Skill Use this skill when: - Evaluating research papers for quality and rigor - Assessing literature review comprehensiveness and quality - Reviewing research methodology design - Scoring data analysis approaches - Evaluating scholarly writing and presentation - Providing structured feedback on academic work - Benchmarking research quality against established criteria ## Evaluation Workflow ### Step 1: Initial Assessment and Scope Definition Begin by identifying the type of scholarly work being evaluated and the evaluation scope: **Work Types:** - Full research paper (empirical, theoretical, or review) - Research proposal or protocol - Literature review (systematic, narrative, or scoping) - Thesis or dissertation chapter - Conference abstract or short paper **Evaluation Scope:** - Comprehens

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Evaluation Workflow
  4. Step 1: Initial Assessment and Scope Definition
  5. Step 2: Dimension-Based Evaluation
  6. Step 3: Scoring and Rating
  7. Step 4: Synthesize Overall Assessment
  8. Step 5: Provide Actionable Feedback
  9. Step 6: Contextual Considerations
  10. Resources
  11. references/evaluationframework.md
  12. scripts/calculatescores.py
  13. Best Practices
  14. Example Evaluation Workflow
Ships with 1 file
  • metadata.json
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About this skill
What does the scholar-evaluation skill do?

Systematic framework for evaluating scholarly and research work based on the ScholarEval methodology. This skill should be used when assessing research papers, evaluating literature reviews, scoring research methodologies, analyzing scientific writing quality, or applying structured evaluation criteria to academic work. Provides comprehensive assessment across multiple dimensions including problem formulation, literature review, methodology, data collection, analysis, results interpretation, and scholarly writing quality.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill scholar-evaluation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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