paper-analysis

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