vasp-dft-executor
VASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials
Profile →npx skills add a5c-ai/babysitter --skill vasp-dft-executor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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": "num
- Purpose
- Capabilities
- Usage Guidelines
- DFT Calculation Workflow
- Process Integration
- Input Schema
- Output Schema
What does the vasp-dft-executor skill do?
VASP DFT calculation skill for electronic structure, geometry optimization, and property prediction of nanomaterials
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill vasp-dft-executor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.