| name | scientific-thinking-scholar-evaluation |
| description | Structured rubric-based evaluation of scholarly work: methodology, evidence quality, citation support, and limitations. USE WHEN reviewing a paper, proposal, thesis chapter, or literature review, checking whether claims are backed by cited evidence, comparing papers, or producing revision feedback. |
| origin | community |
| cluster | research-knowledge |
| version | 1.0.0 |
Scholar Evaluation
Use this skill to evaluate academic or scientific work with a repeatable rubric.
When to Use
- Reviewing a research paper, proposal, thesis chapter, or literature review.
- Checking whether claims are supported by cited evidence.
- Evaluating methodology, study design, analysis, or limitations.
- Comparing two or more papers for quality or relevance.
- Producing structured feedback for revision.
Evaluation Scope
Start by identifying the artifact:
- empirical research paper
- theoretical paper
- technical report
- systematic or narrative literature review
- research proposal
- thesis or dissertation chapter
- conference abstract or short paper
Then choose scope:
- comprehensive: all rubric dimensions
- targeted: one or two dimensions, such as method or citations
- comparative: rank multiple works against the same rubric
Rubric
Score each applicable dimension from 1 to 5:
- 5: excellent; clear, rigorous, and publication-ready
- 4: good; minor improvements needed
- 3: adequate; meaningful gaps but usable
- 2: weak; substantial revision needed
- 1: poor; major validity or clarity problems
Use N/A for dimensions that do not apply.
1. Problem and Research Question
- Is the problem clear and specific?
- Is the contribution meaningful?
- Are scope and assumptions explicit?
- Does the question match the claimed contribution?
2. Literature and Context
- Is relevant prior work covered?
- Does the work synthesize rather than merely list sources?
- Are gaps accurately identified?
- Are recent and foundational sources balanced?
3. Methodology
- Does the method answer the research question?
- Are design choices justified?
- Are variables, datasets, participants, or materials described clearly?
- Could another researcher reproduce the work?
- Are ethical and practical constraints acknowledged?
4. Data and Evidence
- Are data sources credible and appropriate?
- Is sample size or corpus coverage adequate?
- Are inclusion, exclusion, and preprocessing decisions documented?
- Are missing data and bias risks discussed?
5. Analysis
- Are statistical, qualitative, or computational methods appropriate?
- Are baselines and controls fair?
- Are uncertainty, sensitivity, or robustness checks included when needed?
- Are alternative explanations considered?
6. Results and Interpretation
- Are results clearly presented?
- Do claims stay within the evidence?
- Are figures, tables, and metrics understandable?
- Are negative or null results handled honestly?
7. Limitations and Threats to Validity
- Are limitations specific rather than generic?
- Are internal, external, construct, and conclusion-validity risks addressed?
- Does the paper distinguish speculation from demonstrated results?
8. Writing and Structure
- Is the argument easy to follow?
- Are sections organized around the research question?
- Are definitions and notation clear?
- Is the tone precise and scholarly?
9. Citations
- Do cited papers support the claims attached to them?
- Are primary sources used where possible?
- Are reviews labeled as reviews?
- Are preprints labeled as preprints?
- Are citation metadata and links correct?
Review Process
- Read the abstract, introduction, figures, and conclusion for claimed
contribution.
- Read methods and results for evidence quality.
- Check the strongest claims against cited sources.
- Score each applicable dimension.
- Separate critical blockers from revision suggestions.
- End with concrete next edits.
Output Template
# Scholar Evaluation: <Artifact>
## Overall Assessment
- Overall score: <1-5 or N/A>
- Confidence: <high | medium | low>
- Summary: <3-5 sentences>
## Dimension Scores
| Dimension | Score | Evidence | Revision priority |
| --- | ---: | --- | --- |
| Problem and question | | | |
| Literature and context | | | |
| Methodology | | | |
| Data and evidence | | | |
| Analysis | | | |
| Results and interpretation | | | |
| Limitations | | | |
| Writing and structure | | | |
| Citations | | | |
## Critical Issues
## Recommended Revisions
## Evidence Checks Needed
Pitfalls
- Do not use the score as a substitute for concrete feedback.
- Do not penalize a paper for omitting a dimension outside its scope.
- Do not treat citation count, venue, or author reputation as proof of quality.
- Do not accept unsupported claims just because they appear in the abstract.
