How do I install the Vasp Ase skill?

Run npx skillmds@latest add majiayu000/vasp-ase in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Vasp Ase safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Vasp Ase?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Vasp Ase free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Vasp Ase?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Vasp Ase by majiayu000 — Agent Skill

Name: Vasp Ase
Rating: 4.2 (5 reviews)
Author: majiayu000

File contents

VASP ASE Skill

This skill allows the agent to interface with VASP on high-performance computing (HPC) systems like the DGX A100. It focuses on using ASE as the wrapper for clean Pythonic control.

🛠 Prerequisites

Environment Variables: VASP_PP_PATH must point to the directory containing potpaw_PBE, etc.
Dependencies: ase and pymatgen (optional but recommended for analysis) must be installed in the (base) conda environment.
VASP Executable: Access to vasp_std, vasp_gam, or vasp_ncl.

📜 Execution Instructions

1. Setup & Initialization

Always initialize the VASP calculator using the ase.calculators.vasp.Vasp class.

Default Check: If the user doesn't specify, use xc='PBE', kpts=(4, 4, 4), and encut=520.
Parallelization: On this DGX system, use mpirun or srun. Example command: command='mpirun -np 16 vasp_std > vasp.out'

2. Geometry Optimization Template

from ase.io import read
from ase.calculators.vasp import Vasp
from ase.optimize import BFGS

atoms = read('POSCAR')
calc = Vasp(directory='run_dir',
            command='mpirun -np 16 vasp_std',
            xc='PBE',
            encut=520,
            ismear=0,
            sigma=0.05,
            lreal='Auto',
            nsw=100,
            ibrion=2)
atoms.set_calculator(calc)
energy = atoms.get_potential_energy()

3. Error Handling & Troubleshooting

If a calculation fails, the agent should parse OUTCAR or stdout and apply these fixes:

Error/Issue	Diagnostic	Fix Strategy
Electronic Convergence	`NELM` reached without `dE < ediff`	Set `ALGO = Normal` or `Fast`; increase `NELM` to 100; try `AMIX = 0.2`.
Ionic Convergence	Max steps reached	Restart from the last `CONTCAR`; check if forces are oscillating.
Memory/A100 Crash	Segmentation fault	Reduce `NCORE` or `KPAR`; ensure `LREAL = Auto`.
Missing POTCAR	`RuntimeError: POTCAR not found`	Verify `VASP_PP_PATH` is exported in `~/.bashrc`.

🧪 Validation Step

Before running large productions, the agent should run a "Dry Run" by setting LSTOP = .TRUE. in the INCAR or running a single-point energy on a 2-atom cell to verify the environment pathing.

📂 Output Management

Always capture energy_free, forces, and stress.
Store results in a structured JSON or CSV for the user to download from the DGX server.

---name: vasp-asedescription: Professional skill for setting up, executing, and debugging VASP DFT calculations using the Atomic Simulation Environment (ASE).--- # VASP ASE Skill This skill allows the agent to interface with VASP on high-performance computing (HPC) systems like the DGX A100. It focuses on using ASE as the wrapper for clean Pythonic control. ## 🛠 Prerequisites - **Environment Variables:** `VASP_PP_PATH` must point to the directory containing `potpaw_PBE`, etc. - **Dependencies:** `ase` and `pymatgen` (optional but recommended for analysis) must be installed in the `(base)` conda environment. - **VASP Executable:** Access to `vasp_std`, `vasp_gam`, or `vasp_ncl`. ## 📜 Execution Instructions ### 1. Setup & Initialization Always initialize the VASP calculator using the `ase.calculators.vasp.Vasp` class. - **Default Check:** If the user doesn't specify, use `xc='PBE'`, `kpts=(4, 4, 4)`, and `encut=520`. - **Parallelization:** On this DGX system, use `mpirun` or `srun`. Example command: `command='mpirun -np 16 vasp_std > vasp.out'` ### 2. Geometry Optimization Template ```python from ase.io import read from ase.calculators.vasp import Vasp from ase.optimize import BFGS atoms = read('POSCAR') calc = Vasp(directory='run_dir', command='mpirun -np 16 vasp_std', xc='PBE', encut=520, ismear=0, sigma=0.05, lreal='Auto', nsw=100, ibrion=2) atoms.set_calculator(calc) energy = atoms.get_potential_energy() ``` ### 3. Error Handling & Troubleshooting If a calculation fails, the agent should parse `OUTCAR` or `stdout` and apply these fixes: | Error/Issue | Diagnostic | Fix Strategy | | :--- | :--- | :--- | | **Electronic Convergence** | `NELM` reached without `dE < ediff` | Set `ALGO = Normal` or `Fast`; increase `NELM` to 100; try `AMIX = 0.2`. | | **Ionic Convergence** | Max steps reached | Restart from the last `CONTCAR`; check if forces are oscillating. | | **Memory/A100 Crash** | Segmentation fault | Reduce `NCORE` or `KPAR`; ensure `LREAL = Auto`. | | **Missing POTCAR** | `RuntimeError: POTCAR not found` | Verify `VASP_PP_PATH` is exported in `~/.bashrc`. | ## 🧪 Validation Step Before running large productions, the agent should run a "Dry Run" by setting `LSTOP = .TRUE.` in the INCAR or running a single-point energy on a 2-atom cell to verify the environment pathing. ## 📂 Output Management - Always capture `energy_free`, `forces`, and `stress`. - Store results in a structured JSON or CSV for the user to download from the DGX server. ```

Frequently asked questions

Vasp Ase