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scientific-toolkit-skill

Write and verify MATLAB and Python code for scientific computing, statistics, simulation, and publication figures.

Updated Aug 12, 2026
Search Tags:#python#data analysis#simulation#signal processing#scientific computing#publication figures#matlab
One-click install
npx skills add https://github.com/littlt-momo-c-yfc/skills --skill scientific-toolkit-skill-littlt-momo-c-yfc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-toolkit-skill
Source: https://github.com/littlt-momo-c-yfc/skills/tree/main/skills/scientific-toolkit-skill
Command: npx skills add https://github.com/littlt-momo-c-yfc/skills --skill scientific-toolkit-skill-littlt-momo-c-yfc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, pandas, matplotlib, seaborn, scikit-learn, statsmodels, sympy, networkx, pymatgen, qutip, simpy, pymoo, astropy, and includes references (resource) components.

What problem does it solve? Researchers in optoelectronics and related fields often need to write, debug, and verify MATLAB or Python code for signal processing, data analysis, simulation, and publication-quality figures, while avoiding fabricated parameters and irreproducible results. ## Core Features & Use Cases - MATLAB/Octave Support: Debug, refactor, and extend scripts for FFT, filtering, matrix computation, and simulation, with reproducible rng seeds and high-resolution PNG/SVG figure export. - Python Scientific Modules: Load focused references for NumPy, SciPy, pandas, matplotlib, seaborn, scikit-learn, statsmodels, SymPy, QuTiP, pymatgen, NetworkX, and more, covering statistics, optimization, discrete-event simulation, quantum optics, and materials analysis. - Literature & Citation Support: Look up papers, verify citation metadata, and manage BibTeX entries when they support coding or research analysis. - Use Case: A graduate student analyzing BOTDR fiber-sensing time-series data can get a verified Python pipeline that filters the signal, fits a model with statsmodels, and exports publication-ready figures with correct axes, units, and legends. ## Quick Start Ask the agent to analyze your sensor dataset and generate a reproducible Python or MATLAB script with publication-quality figures.

Frequently Asked Questions about scientific-toolkit-skill

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

FAQPage Schema
How do I create publication-quality figures in MATLAB or Python?▼

Export both high-resolution PNG and vector SVG files, and check axes, units, legends, sampling rate, line width, font, and color. In Python, use matplotlib or seaborn with dpi=300 and bbox_inches='tight' for publication output.

What Python libraries should I use for scientific data analysis?▼

Use NumPy and SciPy for numerical computation, pandas for tabular data, matplotlib and seaborn for visualization, statsmodels for statistics, and scikit-learn for machine learning. Specialized needs are covered by SymPy for symbolic math, QuTiP for quantum optics, and pymatgen for materials science.

Can this skill analyze sensor or time-series data from optical experiments?▼

Yes, it supports sensor and time-series analysis including BOTDR/BOTDA fiber sensing, BGS, spectroscopy, and detector data. It covers filtering, deconvolution, calibration, uncertainty handling, and forecasting with statsmodels or TimesFM references.

Does the skill install packages or call external APIs automatically?▼

No, it does not install packages, use cloud APIs, or send data to external services unless the task requires it and the user agrees. Optional installs like uv pip commands and API keys for higher rate limits are only used with explicit consent.

How does the skill ensure reproducible simulation results?▼

It adds rng seeds for stochastic MATLAB simulations and seed parameters for Python random generators, centralizes key parameters, and avoids hardcoded absolute paths. Verification includes running scripts, checking output files, and inspecting plots for plausible dimensions.

When should I use a different skill instead of this one?▼

Use research-writing-skill for manuscript prose and office-academic-skill for Word or PowerPoint deliverables. This skill focuses on research computing, code, data analysis, and figures rather than document authoring.

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