phase-brain-run

Name: phase-brain-run
Availability: InStock
Author: stanislavjiricek

Configure and execute brain model simulations with reproducible parameters and output validation.

6|Updated Mar 8, 2026

Search Tags:#configuration #HPC #simulation #neuroscience #output validation #brain model

Ready to run

npx skills add https://github.com/stanislavjiricek/neuroflow --skill phase-brain-run

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: phase-brain-run
Source: https://github.com/stanislavjiricek/neuroflow/tree/main/skills/phase-brain-run
Command: npx skills add https://github.com/stanislavjiricek/neuroflow --skill phase-brain-run

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides guidance for configuring and executing brain model simulations, ensuring reproducible runs and proper output handling.

Core Features & Use Cases

Simulation Configuration: Guides the creation of explicit and reproducible run parameters via run-config.md.
Output Validation: Ensures immediate sanity checks on simulation outputs (e.g., detecting silence, NaNs, or implausible rates).
Use Case: When preparing to run a complex neural network simulation, use this Skill to ensure all parameters are correctly set, the simulation runs as expected, and the results are validated before saving.

Quick Start

Use the phase-brain-run skill to configure and execute a simulation run for the model located in .neuroflow/brain-build/.

Frequently Asked Questions about phase-brain-run

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

FAQPage Schema

How do I configure reproducible parameters for a brain model simulation?▼

To ensure reproducible brain simulation parameters, you create an explicit `run-config.md` file that defines all execution settings before running the neural network simulation.

What is the best way to validate neural network simulation outputs for errors?▼

Validating neural network simulation outputs involves performing immediate sanity checks to detect anomalies like silence, NaNs, or implausible firing rates before saving the results for analysis.

Can I run a brain simulation without following specific output directory structures?▼

Running a brain simulation requires strict adherence to specific file naming conventions and output directory structures to ensure proper versioning and enable valid downstream analysis of the neural network outputs.

Do I need a pre-built brain model to use this simulation configuration process?▼

Yes, the simulation configuration process is designed for models located in the `.neuroflow/brain-build/` directory, requiring a pre-built brain model structure before execution and validation.

Why does my brain simulation output contain NaNs or implausible firing rates?▼

Brain simulation outputs containing NaNs or implausible firing rates indicate configuration errors or model instabilities, which output validation sanity checks are designed to detect immediately after the run completes.