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vibeflow-scilab

Run headless Scilab batch scripts for parameter calculations and post-processing.

12|1|Updated May 19, 2026
Search Tags:#optimization#headless#control#data-processing#numerical-computing#scilab
One-click install
npx skills add https://github.com/sunrise-hjx/vibeFlow-skills --skill vibeflow-scilab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: vibeflow-scilab
Source: https://github.com/sunrise-hjx/vibeFlow-skills/tree/main/vibeflow-scilab
Command: npx skills add https://github.com/sunrise-hjx/vibeFlow-skills --skill vibeflow-scilab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Scilab-based numerical computing, control, optimization, and data processing are integrated as the backend for VibeCAE, enabling engineers to perform parameter studies, quick analyses, and script-driven workflows without leaving the Scilab environment.

Core Features & Use Cases

  • Parameter calculations and reduced-order analysis from 0-caseDict/caseDict using headless Scilab scripts.
  • Lightweight post-processing and chart generation from solver outputs, with Xcos interface support for dynamic models.
  • Use Case: Rapidly prototype a control-system or signal-processing workflow by encapsulating functions in .sci files and batch scripts.

Quick Start

Generate and run Scilab scripts from 0-caseDict/caseDict to perform parameter calculations and basic post-processing.

Frequently Asked Questions about vibeflow-scilab

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

FAQPage Schema
How do I run headless Scilab scripts for batch numerical computing?▼

Headless Scilab batch execution is enabled by generating and running .sce/.sci scripts from a caseDict, producing structured logs and reproducible parameter calculation outputs without launching the GUI.

What is caseDict-driven parameter study workflow in Scilab?▼

A caseDict-driven workflow uses structured input dictionaries to generate reproducible Scilab numerical computing cases, enabling automated parameter studies, optimization, and control analysis across multiple scenarios.

Can I use Xcos integration for dynamic model control analysis in Scilab?▼

Yes, Xcos interface support is included for dynamic models, allowing you to prototype control-system and signal-processing workflows by encapsulating functions in .sci files and executing batch scripts.

Does this Scilab backend support optimization and data processing without external dependencies?▼

Yes, the Scilab backend operates with zero external dependencies, supporting native optimization, data processing, and numerical computing workflows through batch scripting and reference playbooks.

What is the best way to generate reproducible engineering cases from caseDict in Scilab?▼

The best way is using the structured output pipeline that reads caseDict inputs to drive headless Scilab scripts, automatically generating logs and post-processing artifacts for reproducible case generation.

Why should I use Scilab for numerical computing instead of other data and analytics tools?▼

Scilab provides integrated numerical computing, control analysis, and optimization within a script-driven environment, enabling rapid parameter studies and lightweight post-processing directly from solver outputs.

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