VASP DFT Executor

SkillDev tools

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

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the VASP DFT Executor skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/vasp-dft-executor/SKILL.md and read by ahel’s review.

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

Input Preparation
- Generate structure files
- Select appropriate pseudopotentials
- Set convergence parameters
Calculation Execution
- Monitor convergence
- Check for errors
- Manage computational resources
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

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

Output Schema

{
  "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"
  }
}

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: vasp-dft-executor
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter