materials-physics

Review materials science and physics manuscripts for methodological rigor and reproducibility.

1|Updated Apr 23, 2026
One-click install
npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill materials-physics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: materials-physics
Source: https://github.com/Avaivartika/jiaoleaf-ai/tree/main/extension/skills/science/materials-physics
Command: npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill materials-physics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers in materials science and physics frequently spend substantial time evaluating manuscripts for clarity, methodological rigor, and reproducibility, particularly for simulation-heavy studies and experimental reports.

Core Features & Use Cases

  • Structured review checklist focused on model assumptions, parameter documentation, units consistency, and convergence criteria.
  • Verification of simulation details (timestep, grid, sampling) and characterization methods described in the manuscript.
  • Reproducibility feedback suitable for authors and editors, including suggested clarifications and potential follow-up experiments.

Quick Start

Perform a structured manuscript review by evaluating method clarity, parameter documentation, and data interpretation to identify gaps.

Frequently Asked Questions about materials-physics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review physics manuscripts for simulation reproducibility and methodological rigor?▼

Review physics manuscripts for simulation reproducibility by applying a structured checklist that verifies model assumptions, parameter documentation, units consistency, and convergence criteria to identify methodological gaps.

What should I check when evaluating materials science preprints with heavy simulation data?▼

When evaluating materials science preprints, check simulation details such as timestep, grid, and sampling parameters, alongside characterization methods, to ensure the study's theoretical modeling is fully reproducible.

Can I assess convergence criteria and units consistency in research papers without external tools?▼

You can assess convergence criteria and units consistency in research papers using standard scientific review practices, requiring no external tools beyond a clear articulation of the manuscript's model assumptions and parameters.

What is the best way to provide reproducibility feedback for theoretical modeling manuscripts?▼

The best way to provide reproducibility feedback for theoretical modeling manuscripts is to suggest specific clarifications for parameter documentation and propose potential follow-up experiments suitable for authors and editors.

Does this manuscript review process work for both experimental characterization and theoretical modeling?▼

This manuscript review process works for both experimental characterization and theoretical modeling in materials science and physics, rigorously evaluating method clarity, data interpretation, and parameter documentation across both study types.