Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
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Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
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Stars31,545
Forks3,146
LanguagePython
LicenseMIT
📦 Ships with scientific-agent-skills
</> SKILL.md
scholar-evaluation.SKILL.md
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description: Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
license: MIT license
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---# 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
- 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.
- 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:**
1. **Problem Formulation & Research Questions**
- Clarity and specificity of research questions
- Theoretical or practical significance
- Feasibility and scope appropriateness
- Novelty and contribution potential
2. **Literature Review**
- Comprehensiveness of coverage
- Critical synthesis vs. mere summarization
- Identification of research gaps
- Currency and relevance of sources
- Proper contextualization
3. **Methodology & Research Design**
- Appropriateness for research questions
- Rigor and validity
- Reproducibility and transparency
- Ethical considerations
- Limitations acknowledgment
4. **Data Collection & Sources**
- Quality and appropriateness of data
- Sample size and representativeness
- Data collection procedures
- Source credibility and reliability
5. **Analysis & Interpretation**
- Appropriateness of analytical methods
- Rigor of analysis
- Logical coherence
- Alternative explanations considered
- Results-claims alignment
6. **Results & Findings**
- Clarity of presentation
- Statistical or qualitative rigor
- Visualization quality
- Interpretation accuracy
- Implications discussion
7. **Scholarly Writing & Presentation**
- Clarity and organization
- Academic tone and style
- Grammar and mechanics
- Logical flow
- Accessibility to target audience
8. **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
- 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:
1. **Overall Quality Assessment** - Holistic judgment of the work's scholarly merit
2. **Major Strengths** - 3-5 key strengths across dimensions
3. **Critical Weaknesses** - 3-5 primary areas requiring attention
4. **Priority Recommendations** - Ranked list of improvements by impact
5. **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.
- 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](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.
