aeon
Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classificatio…
Maintainer K-Dense Inc. · Last updated April 1, 2026
Peer review is a systematic process for evaluating scientific manuscripts. Assess methodology, statistics, design, reproducibility, ethics, and reporting standards. Apply this skill for manuscript and grant review across disciplines with constructive, rigorous evaluation.
Original source
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/peer-review
Skill Snapshot
Source Doc
When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
If your document does not already contain schematics or diagrams:
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
The AI will automatically:
When to add schematics:
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
Conduct peer review systematically through the following stages, adapting depth and focus based on the manuscript type and discipline.
Begin with a high-level evaluation to determine the manuscript's scope, novelty, and overall quality.
Key Questions:
Output: Brief summary (2-3 sentences) capturing the manuscript's essence and initial impression.
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