surajinacademia/computational-modeling-skills

Develop, modify, test, or review scientific models and their records, with or without code changes. Use for model formulation, hypothesis testing, numerical verification, and physical validation; coordinate model documents with model-documentation. Exclude generic software engineering, standalone non-model analysis or plotting, and isolated explanations.

Create, style, review, or simplify quantitative plots from completed scientific data, including notebook figures and ordinary paper-ready PDFs. Use the visual gallery, a portable style adapter, and direct plotting templates while preserving scientific identity, weighting, and observable definitions. Do not use for simulation execution, generic data cleaning, inferential modeling, vasculogenesis media, or composite schematic design.

Clarify a problem, help the user work through decisions, confirm the scope, and complete the agreed task. Use when invoked, when the user checks shared understanding, when a request is ambiguous, when they are stuck and ask for help deciding, or when schematic-designer delegates a figure brief. Do not activate for ordinary retrieval or definition requests alone.

Derive, compute, plot, and report physical linear stability analyses for stationary states of 1D or 2D continuum systems. Use for reaction-diffusion, mechanical, curvature, and related spatial dynamical equations requiring analytical dispersion relations, numerical eigenspectra, or a reproducible LaTeX report. Exclude nonlinear time integration and stability analysis of numerical time-stepping schemes.

Plan, write, revise, or audit one physics-focused scientific model document from code, an approved plan, or a maintained methods record. Require approval of the plan and fixed structure before drafting; explain physical rationale, defined notation, equations, and numerical methods, then independently review scientific fidelity and adherence to the standard template. Do not use it for an isolated scientific explanation or question that does not create, edit, restructure, or audit a model document.

Reproduce, assess, or apply a scientific paper's computational model, method, claims, or results. Use for paper-to-code reconstruction, model verification, hypothesis testing, comparison with published experimental or computational evidence, or a requested adaptation. Do not use for a literature summary without an implementation or assessment target.

Generate or reconstruct scientifically faithful figures from specifications, equations, data, or image references. Use for composite publication design, scientific schematics, image reconstruction, or an exact PDF and outlined-SVG contract. Do not use for an ordinary exploratory, diagnostic, comparative, or single scientific data plot; data-visualization owns that path.

Create, maintain, execute, or review Jupyter notebooks for scientific research, theoretical modeling, simulations, and scientific data analysis. Use for new research notebooks and targeted edits to existing .ipynb files; standalone model documents and business dashboards are outside this skill's scope.

Prepare, submit, inspect, and cancel a single CPU batch job using native Slurm commands. Use for a simple portable Slurm job lifecycle; arrays, sweeps, GPU or distributed execution, and scientific model design are outside this skill.