Agent skill

Vasp Relax

VASP geometry optimization (relaxation). An agent skill from Hello-QM/catgo-LRG.

AGPL-3.0Auto-check passed

Install Vasp Relax

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/vasp-relax .claude/skills/vasp-relax && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .claude/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/vasp-relax .agents/skills/vasp-relax && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .agents/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/vasp-relax .cursor/skills/vasp-relax && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .cursor/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/Hello-QM/catgo-LRG.git --path .claude/skills/vasp-relax

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/vasp-relax .gemini/skills/vasp-relax && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .gemini/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/vasp-relax .github/skills/vasp-relax && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .github/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG vasp-relax --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/vasp-relax .opencode/skills/vasp-relax && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "vasp-relax" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-relax into .opencode/skills/vasp-relax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-relax", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: vasp-relax
GitHub stars: 205
Token cost: ~1.9k tokens
SKILL.md length: 521 words
Files: 1
Skills in repo: 75
Repo updated: Sep 22, 2026
First seen: Oct 7, 2026
Licence: AGPL-3.0

At a glance

VASP geometry optimization (relaxation). An agent skill from Hello-QM/catgo-LRG.

SKILL.md covers Discussion Checkpoints, Scenario 1: Bulk Relaxation, Scenario 2: Slab Relaxation… and Scenario 3: Adsorbate on Slab, plus 6 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Vasp Relax is an agent skill from Hello-QM/catgo-LRG. VASP geometry optimization (relaxation). Handles bulk, slab, and adsorbate-on-slab scenarios with correct ISIF, frozen layers, and convergence settings.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AI-driven workbench for computational materials science — interactive 3D structure viewer, natural-language CatBot assistant, visual DAG workflow engine, HPC job submission… The licence is AGPL-3.0.

Example prompts

“/vasp-relax”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit fd6291b. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Vasp Relax loads about 1.9k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 521 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~41
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Hello-QM/catgo-LRG at commit fd6291b, republished under its AGPL-3.0 licence (© Hello-QM). 521 words, ~1,873 tokens.

Download SKILL.mdSave it as .claude/skills/vasp-relax/SKILL.md (or your agent's skills folder).

name: vasp-relax
description: VASP geometry optimization (relaxation). Handles bulk, slab, and adsorbate-on-slab scenarios with correct ISIF, frozen layers, and convergence settings.

VASP Geometry Optimization

Set up and submit VASP geometry optimizations. Three main scenarios with different parameter requirements.

Discussion Checkpoints

🔴 Must discuss with user:

Functional (METAGGA/GGA/+U) — PBE vs SCAN vs PBE+U fundamentally changes energetics; wrong functional invalidates the entire study
ISPIN — must be 2 for magnetic systems (Fe, Co, Ni, Mn oxides, NRR substrates); default ISPIN=1 gives wrong energies for magnetic materials
Structure source — bulk from Materials Project vs user-uploaded CIF vs previous optimization; wrong starting structure wastes all compute

🟡 Recommend confirming:

ENCUT (default: 520) — increase to 600+ for accurate equation of state or when comparing across different compositions
EDIFFG (default: -0.02 eV/A) — tighten to -0.01 for frequency calculations downstream; loosen to -0.05 for quick screening
k-points — must be converged for the system; small unit cells need denser meshes
Selective dynamics / frozen layers (default: freeze_layers=2 for slabs) — adjust based on slab thickness and whether subsurface relaxation matters
ISIF (default: 2) — must be 3 for bulk relaxation, 2 for slabs; wrong ISIF is a common mistake

🟢 Safe defaults:

EDIFF = 1E-5
ISMEAR = 0, SIGMA = 0.05
NSW = 200
IBRION = 2 (conjugate gradient)
PREC = Accurate
NCORE = 4

Scenario 1: Bulk Relaxation

Full cell + ionic relaxation. Use ISIF=3 to allow cell shape and volume to change.

python

from catgo.workflow import Workflow
from catgo.workflow.builtins import geo_opt

wf = Workflow("Bulk TiO2 relaxation")
struct = wf.add_task("structure_input", structure=bulk_json)
opt = wf.add_task(geo_opt, structure=struct.output.structure,
                  ISIF=3,        # Relax cell shape + volume + ions
                  EDIFFG=-0.02,  # Force convergence (eV/A)
                  system_name="bulk_TiO2")
wf.submit()

Key parameters:

ISIF=3 — relax ions + cell shape + cell volume
EDIFFG=-0.02 — converge when max force < 0.02 eV/A (negative = force criterion)
NSW=200 — max ionic steps (default, usually converges in 50-100)

MCP equivalent:

catgo_workflow_engine(action="create", params={"name": "Bulk TiO2"})

catgo_workflow_engine(action="add_task", params={
  "workflow_id": "wf_xxx",
  "task_type": "structure_input",
  "name": "input",
  "structure": "<bulk_json>"
})

catgo_workflow_engine(action="add_task", params={
  "workflow_id": "wf_xxx",
  "task_type": "geo_opt",
  "software": "vasp",
  "structure": "{{t_001.output.structure}}",
  "ISIF": 3,
  "system_name": "bulk_TiO2"
})

catgo_workflow_engine(action="submit", params={"workflow_id": "wf_xxx"})

Scenario 2: Slab Relaxation (Clean Surface)

Fixed cell, relax only ions. Bottom layers frozen to mimic bulk.

python

wf = Workflow("RuO2(110) slab")
struct = wf.add_task("structure_input", structure=slab_json)
opt = wf.add_task(geo_opt, structure=struct.output.structure,
                  ISIF=2,              # Fix cell, relax ions only
                  selective_dynamics=True,
                  freeze_layers=2,     # Freeze bottom 2 layers
                  system_name="clean_slab")
wf.submit()

Key parameters:

ISIF=2 — MANDATORY for slabs. Fixes cell shape and volume
freeze_layers=2 — freeze bottom N layers (sorted by z-coordinate)
selective_dynamics=True — enable per-atom freeze in POSCAR
Vacuum: ensure >= 15 A in z-direction to avoid periodic image interaction

ISIF reference:

ISIF	Ions	Cell shape	Cell volume	Use case
2	Yes	No	No	Slabs, adsorbates
3	Yes	Yes	Yes	Bulk relaxation
4	Yes	Yes	No	Bulk at fixed volume

Show full SKILL.md (208 more words)Show less

Scenario 3: Adsorbate on Slab

Same as slab relaxation, but the structure has an adsorbate. Adsorbate atoms are always free.

python

wf = Workflow("OH on RuO2(110)")
struct = wf.add_task("structure_input", structure=adsorbate_slab_json)
opt = wf.add_task(geo_opt, structure=struct.output.structure,
                  ISIF=2,
                  selective_dynamics=True,
                  freeze_layers=2,
                  EDIFFG=-0.02,
                  system_name="*OH")
wf.submit()

Guidelines for adsorbates:

freeze_layers only affects the slab — adsorbate atoms above the surface are always relaxed
Use system_name="*OH" convention (asterisk = adsorbed species)
For weak adsorbates (CO2, H2O physisorption), add IVDW=11 for DFT-D3

Confirmation Gate

By default, HPC tasks (including VASP relaxation) pause at PENDING_REVIEW after local preprocessing completes. This lets users verify the structure, frozen layers, and VASP parameters in the task detail panel before committing HPC resources. Click "Confirm & Submit" in the UI, or use wf.submit(auto_submit=True) to bypass the gate.

Visual Verification Steps

Before submitting, verify the structure in the viewer:

# Step 1: Check current structure in viewer
catgo_view(action="get_state")
# Verify: correct composition, reasonable cell parameters, vacuum > 15 A for slabs

# Step 2: For slabs, verify frozen atoms
catgo_view(action="get_state")
# Check that bottom-layer atoms will be frozen

# Step 3: After optimization completes, push result to viewer
catgo_workflow_engine(action="get_result", params={"task_id": "t_opt"})
catgo_view(action="push", params={"structure": "<optimized_structure_json>"})

Convergence Monitoring

# Check if optimization is converged
catgo_analyze(action="convergence", params={"task_id": "t_opt"})
# Returns: energy vs step, max force vs step, whether converged

# Check remaining forces
catgo_analyze(action="forces", params={"task_id": "t_opt"})
# Returns: per-atom forces, max force, force on each species

Common Chain: Relaxation then Frequency

For thermodynamic properties (Gibbs energy, ZPE), chain relaxation with frequency:

python

from catgo.workflow.builtins import geo_opt, freq, gibbs_energy

wf = Workflow("OH adsorption thermodynamics")
struct = wf.add_task("structure_input", structure=slab_oh_json)

opt = wf.add_task(geo_opt, structure=struct.output.structure,
                  ISIF=2, freeze_layers=2, system_name="*OH")

frq = wf.add_task(freq, structure=opt.output.structure,
                  freeze_mode="layers", freeze_layers=4,
                  system_name="*OH")

gib = wf.add_task(gibbs_energy,
                  energy=opt.output.energy,
                  frequencies=frq.output.frequencies,
                  phase="adsorbed", system_name="*OH")

wf.submit()

Troubleshooting

Problem	Fix
Forces not converging	Increase NSW (e.g., 400), or loosen EDIFFG to -0.03
Atoms escaping into vacuum	Check initial adsorbate placement, reduce POTIM to 0.3
SCF not converging	Switch ALGO=All, increase NELM=400, try AMIX=0.1
Cell shape changing for slab	Ensure ISIF=2, not ISIF=3
Wrong energy (magnetic system)	Set ISPIN=2, provide MAGMOM

Parameter Defaults (inherited from config)

These are applied automatically unless overridden:

ENCUT=520, EDIFF=1e-5, PREC=Accurate
IBRION=2 (conjugate gradient), NSW=200
EDIFFG=-0.02, ISIF=2
ISMEAR=0, SIGMA=0.05 (Gaussian smearing)
NCORE=4, LREAL=Auto

Files

Just SKILL.md in .claude/skills/vasp-relax of Hello-QM/catgo-LRG.

Open the folder on GitHubat commit fd6291b

Compare with similar skills

Vasp Relax next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Vasp Relax compared with similar skills
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Error Handlingthedaviddias/Front-End-Checklist	74k	—	~416	Automated safety check: Pass	MIT	4 days ago
Error Handlingaffaan-m/ECC	276k	—	~2.4k	Automated safety check: Pass	MIT	yesterday
Python Error Handlingwshobson/agents	40k	—	~1.5k	Automated safety check: Pass	MIT	6 days ago
Error Handling Patternswshobson/agents	40k	11 repos	~1k	Automated safety check: Pass	MIT	6 days ago

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Questions about Vasp Relax

What does Vasp Relax do?

VASP geometry optimization (relaxation). An agent skill from Hello-QM/catgo-LRG. Vasp Relax is an agent skill from Hello-QM/catgo-LRG. VASP geometry optimization (relaxation).

How do I install Vasp Relax in Claude Code?

Run `npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a claude-code`. Or copy the skill folder (.claude/skills/vasp-relax in Hello-QM/catgo-LRG) into .claude/skills/vasp-relax in your project. Claude Code loads it when a task matches its description.

How do I install Vasp Relax in Codex?

Run `npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a codex`. Or copy the skill folder (.claude/skills/vasp-relax in Hello-QM/catgo-LRG) into .agents/skills/vasp-relax in your project. Codex loads it when a task matches its description.

Can I use Vasp Relax in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Hello-QM/catgo-LRG --skill vasp-relax -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vasp-relax, .gemini/skills/vasp-relax, .github/skills/vasp-relax and .opencode/skills/vasp-relax in your project.

What does Vasp Relax need to run?

SKILL.md names no scripts, command-line tools or credentials: Vasp Relax is instructions for the agent only. Our summary lists: Python 3.

Does Vasp Relax access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Vasp Relax safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Vasp Relax use?

Vasp Relax is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vasp Relax use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Vasp Relax?

Skills that share tags, products or a category with Vasp Relax: Error Handling (affaan-m/ECC, 277k stars), Error Handling (thedaviddias/Front-End-Checklist, 74k stars), Error Handling (affaan-m/ECC, 276k stars) and Python Error Handling (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vasp Relax?

Hello-QM (a GitHub user) maintains it in Hello-QM/catgo-LRG, which has 205 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on September 22, 2026.

Source: Hello-QM/catgo-LRG on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Vasp Relax

Facts

At a glance

What it does

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

VASP Geometry Optimization

Discussion Checkpoints

Scenario 1: Bulk Relaxation

Scenario 2: Slab Relaxation (Clean Surface)

Scenario 3: Adsorbate on Slab

Confirmation Gate

Visual Verification Steps

Convergence Monitoring

Common Chain: Relaxation then Frequency

Troubleshooting

Parameter Defaults (inherited from config)

Files

Compare with similar skills

Similar skills

More from Hello-QM/catgo-LRG

Questions about Vasp Relax