vasp-dft-executor

VASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials

509 stars

Best use case

vasp-dft-executor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

VASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials

Teams using vasp-dft-executor should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/vasp-dft-executor/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/nanotechnology/skills/vasp-dft-executor/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/vasp-dft-executor/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How vasp-dft-executor Compares

Feature / Agentvasp-dft-executorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

VASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# VASP DFT Executor

## Purpose

The VASP DFT Executor skill provides density functional theory calculation capabilities using VASP for nanomaterial property prediction, enabling electronic structure analysis, geometry optimization, and materials property computation.

## Capabilities

- Input file generation (INCAR, POSCAR, KPOINTS, POTCAR)
- Geometry optimization
- Electronic band structure calculation
- Density of states analysis
- Formation energy calculation
- Optical property prediction

## Usage Guidelines

### DFT Calculation Workflow

1. **Input Preparation**
   - Generate structure files
   - Select appropriate pseudopotentials
   - Set convergence parameters

2. **Calculation Execution**
   - Monitor convergence
   - Check for errors
   - Manage computational resources

3. **Result Analysis**
   - Extract electronic properties
   - Analyze band structure
   - Calculate derived properties

## Process Integration

- DFT Calculation Pipeline for Nanomaterials
- Multiscale Modeling Integration
- Machine Learning Materials Discovery Pipeline

## Input Schema

```json
{
  "structure_file": "string (POSCAR/CIF)",
  "calculation_type": "relax|static|band|dos|optical",
  "functional": "PBE|HSE06|SCAN",
  "kpoint_density": "number",
  "encut": "number (eV)"
}
```

## Output Schema

```json
{
  "total_energy": "number (eV)",
  "bandgap": "number (eV)",
  "formation_energy": "number (eV/atom)",
  "optimized_structure": "string (CONTCAR)",
  "electronic_properties": {
    "dos_file": "string",
    "band_file": "string"
  },
  "convergence": {
    "energy_converged": "boolean",
    "force_converged": "boolean"
  }
}
```

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