vasp-batch-execution

Submit prepared VASP jobs and collect outputs with failure evidence.

13|1|Updated Nov 27, 2025
One-click install
npx skills add https://github.com/q734738781/CatMaster --skill vasp-batch-execution
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vasp-batch-execution
Source: https://github.com/q734738781/CatMaster/tree/main/skills/vasp-batch-execution
Command: npx skills add https://github.com/q734738781/CatMaster --skill vasp-batch-execution

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill prevents corruption of input calculation trees and loss of failure evidence when dispatching many prepared VASP jobs, ensuring runs are staged, collected, and triaged safely.

Core Features & Use Cases

  • Layout Validation: Detects valid calc folders by presence of INCAR and POTCAR, distinguishes single-folder and recursive batch modes, and rejects nested or overlapping calc roots.
  • Safe Submission & Collection: Stages work under a fresh output tree, injects a bootstrap dispatcher, dispatches via the scheduler, and collects results into a final output snapshot rather than mutating inputs.
  • Minimal Failure Triage: Prioritizes reading _BATCH_STATE.json and focused scheduler/stdout/stderr evidence, enabling rerun of only failed subsets into a fresh output root.
  • Use Case: Submit a directory of DFT calculations for a high-throughput campaign while preserving clear failure evidence for selective reruns.

Quick Start

Submit prepared VASP jobs from input_dir into a separate output_dir using vasp_execute_batch and collect results while preserving _BATCH_STATE.json for focused failure triage.

Frequently Asked Questions about vasp-batch-execution

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

FAQPage Schema
How do I safely batch submit VASP jobs without corrupting my input directories?

To safely batch submit VASP jobs, stage work under a fresh output tree separate from your input calculation folders. This approach collects results into a final output snapshot, preventing any mutation or corruption of the original input directory structure.

How does failure triage work for batch VASP calculations?

Failure triage for batch VASP calculations relies on reading the _BATCH_STATE.json file alongside focused scheduler, stdout, and stderr evidence. This prioritization preserves failure evidence and enables the selective rerun of only the failed subsets.

What's the best way to identify valid VASP calc folders for recursive job dispatch?

Valid VASP calc folders for recursive job dispatch are identified by the presence of INCAR and POTCAR files. Layout validation distinguishes between single-folder and recursive batch modes while rejecting nested or overlapping calculation roots.

Can I rerun only the failed subsets from a high-throughput VASP campaign?

Yes, you can rerun failed subsets from a VASP campaign by using vasp_execute_batch to dispatch the failed jobs into a fresh output root. The system reads _BATCH_STATE.json to identify failures and selectively reruns them without touching successful calculations.

Why must the output_dir be separate from the input_dir in VASP batch execution?

The output_dir must be separate from the input_dir to prevent output roots from existing inside input roots. This layout rule ensures the bootstrap dispatcher stages work safely, avoiding nested or overlapping calculation trees that corrupt input data.