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convergence-test

Automate ENCUT and KPOINTS convergence testing in DFT workflows via CatGo.

181|20|Updated Apr 29, 2026
Search Tags:#workflow#convergence#kpoints#parameter-sweep#encut#single_point
One-click install
npx skills add https://github.com/Hello-QM/catgo-LRG --skill convergence-test-hello-qm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: convergence-test
Source: https://github.com/Hello-QM/catgo-LRG/tree/main/server/catgo/workflow/skills/analysis/convergence
Command: npx skills add https://github.com/Hello-QM/catgo-LRG --skill convergence-test-hello-qm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Convergence-test helps computational workflows verify that numerical parameters (ENCUT and KPOINTS) do not bias results, ensuring reliable production calculations.

Core Features & Use Cases

  • Fan-out DAG workflows to run multiple single_point tasks with different ENCUT values and/or KPOINTS meshes.
  • Clear guidance for ENCUT and KPOINTS convergence, two-stage strategies, and convergence criteria.
  • Step-by-step workflow example and practical use cases for TiO2 and slab systems.

Quick Start

Initiate an ENCUT convergence study by creating a new workflow, add single_point tasks for ENCUT values 300, 400, 500, 600, and 700, and submit the workflow for execution.

Frequently Asked Questions about convergence-test

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

FAQPage Schema
How do I automate convergence testing for ENCUT and KPOINTS in DFT workflows?▼

DFT convergence testing is automated by fanning out multiple single_point tasks with varying ENCUT or KPOINTS, submitting them via API, and analyzing the results to determine converged values.

What is the best way to verify that numerical parameters do not bias my DFT results?▼

Verifying that numerical parameters do not bias DFT results involves running multiple single_point tasks across varying ENCUT or KPOINTS meshes, then applying a defined convergence criteria to the retrieved results.

Do I need the CatGo workflow engine to run ENCUT and KPOINTS convergence studies?▼

Running ENCUT and KPOINTS convergence studies requires the CatGo workflow engine to handle the creation, submission, and retrieval of the fan-out DAG single_point tasks.

How do I set up a two-stage convergence strategy for slab systems?▼

A two-stage convergence strategy for slab systems uses a fan-out DAG workflow to run separate single_point task sweeps for ENCUT and KPOINTS, followed by result analysis against defined convergence criteria.

What are the limitations when running a KPOINTS convergence sweep?▼

KPOINTS convergence sweeps depend on the CatGo workflow engine to manage the fan-out DAG of single_point tasks and require a clearly defined convergence criteria to evaluate the retrieved API results.

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