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beita6969 / paper-analysis

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".

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SKILL.md
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Paper Analysis

Systematic scientific paper reading, summarization, and critical analysis.

Paper Acquisition

  1. If user provides a DOI: fetch via https://doi.org/DOI or Semantic Scholar API
  2. If user provides arXiv ID: fetch via https://arxiv.org/abs/ID
  3. If user provides a URL: use web_fetch to extract content
  4. 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:

DimensionPaper APaper BPaper 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