Installable skillMIT

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 o...

BY beita6969UPDATED Oct 27, 2026
INTENDED FOR◈OpenClawInstall in a listed agent.

instructions.md

---
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

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
COMPATIBILITY & REFERENCES

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.