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".
Best use case
paper-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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".
Teams using paper-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/paper-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How paper-analysis Compares
| Feature / Agent | paper-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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: | 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
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