| name | paper-analysis |
| description | Read, summarize, and critically analyze scientific papers. Extract key findings, methodology, limitations, and contributions. Use when user shares a paper (PDF/URL/DOI), asks to summarize a paper, critique methodology, extract data from a paper, compare papers, or do a critical review. Triggers on "summarize this paper", "analyze this study", "what does this paper say", "critique this methodology", "extract findings from". |
Paper Analysis
Systematic scientific paper reading, summarization, and critical analysis.
Paper Acquisition
- If user provides a DOI: fetch via
https://doi.org/DOI or Semantic Scholar API
- If user provides arXiv ID: fetch via
https://arxiv.org/abs/ID
- If user provides a URL: use
web_fetch to extract content
- If user provides a PDF file: read directly or use summarize skill
Analysis Framework
Quick Summary (default)
Provide in ~200 words:
- Research question / objective
- Method (1-2 sentences)
- Key findings (2-3 bullet points)
- Main contribution
- One key limitation
Deep Analysis
When requested, provide structured analysis:
1. Paper Metadata
- Title, authors, year, journal/venue, DOI
- Citation count (via Semantic Scholar)
2. Research Context
- Problem statement and motivation
- Research gap being addressed
- Theoretical framework
3. Methodology Assessment
- Study design (experimental/observational/computational/theoretical)
- Sample/dataset description
- Variables (independent, dependent, controls)
- Analysis methods
- Reproducibility assessment (data/code availability)
4. Results Evaluation
- Key findings with effect sizes and confidence intervals
- Statistical significance vs practical significance
- Figures and tables interpretation
- Are results consistent with claims?
5. Critical Assessment
Check for:
- Internal validity: confounds, selection bias, measurement error
- External validity: generalizability, ecological validity
- Statistical issues: multiple comparisons, p-hacking, small N
- Logical issues: correlation ≠ causation, survivorship bias
- Reporting issues: selective reporting, missing negative results
- Methodological rigor: appropriate controls, blinding, randomization
6. Contribution & Impact
- Novelty assessment
- Practical implications
- Theoretical implications
- Future directions suggested
Comparison Mode
When comparing multiple papers:
| Dimension | Paper A | Paper B | Paper C |
|---|
| Research Question | | | |
| Method | | | |
| Sample Size | | | |
| Key Finding | | | |
| Limitation | | | |
| Strength | | | |
Domain-Specific Checklists
RCT (Randomized Controlled Trial)
- CONSORT checklist compliance
- Randomization method, allocation concealment
- Blinding (single/double/triple)
- ITT vs per-protocol analysis
- Dropout rates and handling
Observational Studies
- STROBE checklist
- Confounding control methods
- Selection bias assessment
Machine Learning Papers
- Train/val/test split methodology
- Baseline comparisons
- Ablation studies
- Statistical significance of improvements
- Computational cost reporting
- Code/data availability
Qualitative Research
- Sampling strategy (purposive, theoretical, snowball)
- Data saturation
- Coding methodology (thematic, grounded theory)
- Reflexivity and positionality
- Member checking / triangulation
Output Style
- Use academic but accessible language
- Cite specific sections/figures/tables from the paper
- Distinguish between what the paper claims and what the evidence supports
- Flag any red flags clearly but diplomatically
