scholar-evaluation

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

Assessing publication readiness for target venues

Providing quantitative evaluation to complement qualitative peer review

Visual Enhancement with Scientific Schematics

When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.

If your document does not already contain schematics or diagrams:

Use the scientific-schematics skill to generate AI-powered publication-quality diagrams

Simply describe your desired diagram in natural language

Nano Banana Pro will automatically generate, review, and refine the schematic

For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.

How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

The AI will automatically:

Create publication-quality images with proper formatting

Review and refine through multiple iterations

Ensure accessibility (colorblind-friendly, high contrast)

Save outputs in the figures/ directory

When to add schematics:

Evaluation framework diagrams

Quality assessment criteria decision trees

Scholarly workflow visualizations

Assessment methodology flowcharts

Scoring rubric visualizations

Evaluation process diagrams

Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

---

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:

Comprehensive (all dimensions)

Targeted (specific aspects like methodology or writing)

Comparative (benchmarking against other work)

Ask the user to clarify if the scope is ambiguous.

Step 2: Dimension-Based Evaluation

Systematically evaluate the work across the ScholarEval dimensions. For each applicable dimension, assess quality, identify strengths and weaknesses, and provide scores where appropriate.

Refer to references/evaluation_framework.md for detailed criteria and rubrics for each dimension.

Core Evaluation Dimensions:

Problem Formulation & Research Questions

- Clarity and specificity of research questions
- Theoretical or practical significance
- Feasibility and scope appropriateness
- Novelty and contribution potential

Literature Review

- Comprehensiveness of coverage
- Critical synthesis vs. mere summarization
- Identification of research gaps
- Currency and relevance of sources
- Proper contextualization

Methodology & Research Design

- Appropriateness for research questions
- Rigor and validity
- Reproducibility and transparency
- Ethical considerations
- Limitations acknowledgment

Data Collection & Sources

- Quality and appropriateness of data
- Sample size and representativeness
- Data collection procedures
- Source credibility and reliability

Analysis & Interpretation

- Appropriateness of analytical methods
- Rigor of analysis
- Logical coherence
- Alternative explanations considered
- Results-claims alignment

Results & Findings

- Clarity of presentation
- Statistical or qualitative rigor
- Visualization quality
- Interpretation accuracy
- Implications discussion

Scholarly Writing & Presentation

- Clarity and organization
- Academic tone and style
- Grammar and mechanics
- Logical flow
- Accessibility to target audience

Citations & References

- Citation completeness
- Source quality and appropriateness
- Citation accuracy
- Balance of perspectives
- Adherence to citation standards

Step 3: Scoring and Rating

For each evaluated dimension, provide:

Qualitative Assessment:

Key strengths (2-3 specific points)

Areas for improvement (2-3 specific points)

Critical issues (if any)

Quantitative Scoring (Optional):
Use a 5-point scale where applicable:

5: Excellent - Exemplary quality, publishable in top venues

4: Good - Strong quality with minor improvements needed

3: Adequate - Acceptable quality with notable areas for improvement

2: Needs Improvement - Significant revisions required

1: Poor - Fundamental issues requiring major revision

To calculate aggregate scores programmatically, use scripts/calculate_scores.py.

Step 4: Synthesize Overall Assessment

Provide an integrated evaluation summary:

Overall Quality Assessment - Holistic judgment of the work's scholarly merit

Major Strengths - 3-5 key strengths across dimensions

Critical Weaknesses - 3-5 primary areas requiring attention

Priority Recommendations - Ranked list of improvements by impact

Publication Readiness (if applicable) - Assessment of suitability for target venues

Step 5: Provide Actionable Feedback

Transform evaluation findings into constructive, actionable feedback:

Feedback Structure:

Specific - Reference exact sections, paragraphs, or page numbers

Actionable - Provide concrete suggestions for improvement

Prioritized - Rank recommendations by importance and feasibility

Balanced - Acknowledge strengths while addressing weaknesses

Evidence-based - Ground feedback in evaluation criteria

Feedback Format Options:

Structured report with dimension-by-dimension analysis

Annotated comments mapped to specific document sections

Executive summary with key findings and recommendations

Comparative analysis against benchmark standards

Step 6: Contextual Considerations

Adjust evaluation approach based on:

Stage of Development:

Early draft: Focus on conceptual and structural issues

Advanced draft: Focus on refinement and polish

Final submission: Comprehensive quality check

Purpose and Venue:

Journal article: High standards for rigor and contribution

Conference paper: Balance novelty with presentation clarity

Student work: Educational feedback with developmental focus

Grant proposal: Emphasis on feasibility and impact

Discipline-Specific Norms:

STEM fields: Emphasis on reproducibility and statistical rigor

Social sciences: Balance quantitative and qualitative standards

Humanities: Focus on argumentation and scholarly interpretation

Resources

references/evaluation_framework.md

Detailed evaluation criteria, rubrics, and quality indicators for each ScholarEval dimension. Load this reference when conducting evaluations to access specific assessment guidelines and scoring rubrics.

Search patterns for quick access:

"Problem Formulation criteria"

"Literature Review rubric"

"Methodology assessment"

"Data quality indicators"

"Analysis rigor standards"

"Writing quality checklist"

scripts/calculate_scores.py

Python script for calculating aggregate evaluation scores from dimension-level ratings. Supports weighted averaging, threshold analysis, and score visualization.

Usage:

python scripts/calculate_scores.py --scores <dimension_scores.json> --output <report.txt>

Best Practices

Maintain Objectivity - Base evaluations on established criteria, not personal preferences

Be Comprehensive - Evaluate all applicable dimensions systematically

Provide Evidence - Support assessments with specific examples from the work

Stay Constructive - Frame weaknesses as opportunities for improvement

Consider Context - Adjust expectations based on work stage and purpose

Document Rationale - Explain the reasoning behind assessments and scores

Encourage Strengths - Explicitly acknowledge what the work does well

Prioritize Feedback - Focus on high-impact improvements first

Example Evaluation Workflow

User Request: "Evaluate this research paper on machine learning for drug discovery"

Response Process:

Identify work type (empirical research paper) and scope (comprehensive evaluation)

Load references/evaluation_framework.md for detailed criteria

Systematically assess each dimension:

- Problem formulation: Clear research question about ML model performance
- Literature review: Comprehensive coverage of recent ML and drug discovery work
- Methodology: Appropriate deep learning architecture with validation procedures
- [Continue through all dimensions...]

Calculate dimension scores and overall assessment

Synthesize findings into structured report highlighting:

- Strong methodology and reproducible code
- Needs more diverse dataset evaluation
- Writing could improve clarity in results section

Provide prioritized recommendations with specific suggestions

Integration with Scientific Writer

This skill integrates seamlessly with the scientific writer workflow:

After Paper Generation:

Use Scholar Evaluation as an alternative or complement to peer review

Generate SCHOLAR_EVALUATION.md alongside PEER_REVIEW.md

Provide quantitative scores to track improvement across revisions

During Revision:

Re-evaluate specific dimensions after addressing feedback

Track score improvements over multiple versions

Identify persistent weaknesses requiring attention

Publication Preparation:

Assess readiness for target journal/conference

Identify gaps before submission

Benchmark against publication standards

Notes

Evaluation rigor should match the work's purpose and stage

Some dimensions may not apply to all work types (e.g., data collection for purely theoretical papers)

Cultural and disciplinary differences in scholarly norms should be considered

This framework complements, not replaces, domain-specific expertise

Use in combination with peer-review skill for comprehensive assessment

Citation

This skill is based on the ScholarEval framework introduced in:

Moussa, H. N., Da Silva, P. Q., Adu-Ampratwum, D., East, A., Lu, Z., Puccetti, N., Xue, M., Sun, H., Majumder, B. P., & Kumar, S. (2025). _ScholarEval: Research Idea Evaluation Grounded in Literature_. arXiv preprint arXiv:2510.16234. https://arxiv.org/abs/2510.16234

Abstract: ScholarEval is a retrieval augmented evaluation framework that assesses research ideas based on two fundamental criteria: soundness (the empirical validity of proposed methods based on existing literature) and contribution (the degree of advancement made by the idea across different dimensions relative to prior research). The framework achieves significantly higher coverage of expert-annotated evaluation points and is consistently preferred over baseline systems in terms of evaluation actionability, depth, and evidence support.