Lammps
JCLiuGroup/AI-Computational-Chemist
Prepare, run, and validate LAMMPS molecular dynamics. An agent skill from JCLiuGroup/AI-Computational-Chemist.
Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials.
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmd --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/lammps-deepmd .claude/skills/lammps-deepmd && rm -rf skills-srcUse ~/.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/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .claude/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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 install https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmdType 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.
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmd --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/lammps-deepmd .agents/skills/lammps-deepmd && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .agents/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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.
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmd --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/lammps-deepmd .cursor/skills/lammps-deepmd && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .cursor/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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 https://github.com/Hello-QM/catgo-LRG.git --path .claude/skills/lammps-deepmd--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmd --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/lammps-deepmd .gemini/skills/lammps-deepmd && rm -rf skills-srcUse ~/.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/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .gemini/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmdInstalls 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).
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/lammps-deepmd .github/skills/lammps-deepmd && rm -rf skills-srcUse ~/.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/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .github/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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.
$ npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Hello-QM/catgo-LRG lammps-deepmd --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/lammps-deepmd .opencode/skills/lammps-deepmd && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "lammps-deepmd" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/lammps-deepmd into .opencode/skills/lammps-deepmd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lammps-deepmd", 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.
lammps-deepmdRun LAMMPS molecular dynamics with DeePMD-kit machine learning potentials.
Lammps Deepmd is an agent skill from Hello-QM/catgo-LRG. Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials. Use when the user wants MD simulations driven by a trained DP model.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires LAMMPS compiled with the DEEPMD package. A frozen DeePMD model (.pb) is required.
It sits in Data & Analytics, covering Physical and earth sciences and Machine learning. 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.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit fd6291b. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires LAMMPS compiled with the DEEPMD package. A frozen DeePMD model (.pb) is required.
From compatibility in the SKILL.md frontmatter.
Lammps Deepmd loads about 1k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 323 words of instructions outside code blocks.
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.
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.
The full file from Hello-QM/catgo-LRG at commit fd6291b, republished under its AGPL-3.0 licence (© Hello-QM). 323 words, ~1,020 tokens.
.claude/skills/lammps-deepmd/SKILL.md (or your agent's skills folder)..pb model filelmp -h | grep DEEPMD).pb)type_map used during model trainingcatgo_view(action="get_state")catgo_workflow_engine(action="create", params={"name": "LAMMPS DeePMD NVT 300K"})catgo_workflow_engine(action="add_task", params={
"workflow_id": "wf_xxx",
"task_type": "shell",
"name": "lmp_dpmd",
"command": "lmp -in lammps.in > lammps.log 2>&1",
"input_files": {
"lammps.in": "<input script>",
"frozen_model.pb": "{{model_path}}"
},
"system_name": "TiO2_md"
})units metal
boundary p p p
atom_style atomic
read_data structure.lmp
pair_style deepmd frozen_model.pb
pair_coeff * *
neighbor 2.0 bin
neigh_modify every 1 delay 0 check yes
# Velocities
velocity all create 300.0 12345 dist gaussian
# NVT thermostat
fix 1 all nvt temp 300.0 300.0 0.1
# Timestep (ps in metal units)
timestep 0.001
# Output
thermo 100
thermo_style custom step temp pe ke etotal press vol
dump 1 all custom 100 traj.lammpstrj id type x y z fx fy fz
dump_modify 1 sort id
# Restart
restart 10000 restart.*.data
run 100000Replace the fix line:
fix 1 all npt temp 300.0 300.0 0.1 iso 0.0 0.0 1.0For active learning or reliability checking, use multiple models:
pair_style deepmd model_0.pb model_1.pb model_2.pb model_3.pb out_freq 100 out_file model_devi.out
pair_coeff * *This writes model_devi.out with per-frame max/min/avg force deviation. Use thresholds:
max_devi_f < 0.05 eV/Ang: model is reliable0.05 < max_devi_f < 0.15: candidate for active learningmax_devi_f > 0.15: model is unreliable, do not trust resultsConvert from CatGo structure to LAMMPS data format:
from ase.io import read, write
# Read pymatgen dict, write LAMMPS data
atoms = read('structure.json')
write('structure.lmp', atoms, format='lammps-data')Or use dpdata (see data/dpdata/SKILL.md).
| Parameter | Typical value | Notes |
|---|---|---|
| timestep | 0.001 ps (1 fs) | Metal units; can use 2 fs for stiff systems |
| NVT temp damp | 0.1 ps | Nose-Hoover damping; 100x timestep |
| NPT press damp | 1.0 ps | Pressure damping; 1000x timestep |
| dump frequency | 100-1000 | Every 100 steps = 0.1 ps |
| neighbor skin | 2.0 Ang | Rebuild neighbor list threshold |
| run | 100K-10M | Depends on property of interest |
units metal (eV, Ang, ps). Never use units real.pair_style deepmd needs a frozen .pb file. Run dp freeze first.© Hello-QM, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/lammps-deepmd of Hello-QM/catgo-LRG.
Open the folder on GitHubat commit fd6291b
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Hello-QM/catgo-LRG, which our catalogue first saw on October 7, 2026.
Lammps Deepmd 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Lammps Deepmd this skillHello-QM/catgo-LRG | 205 | 1 repos | ~1k | Automated safety check: Pass | AGPL-3.0 | |
| LammpsJCLiuGroup/AI-Computational-Chemist | 145 | 1 repos | ~539 | Automated safety check: Pass | Custom licence | |
| Optimize For GPUmajiayu000/claude-skill-registry | 666 | 1 repos | ~8.5k | Automated safety check: Pass | MIT | |
| DP-GEN Simplify Workflowjinzhezenggroup/computational-chemistry-agent-skills | 148 | — | ~2.7k | Automated safety check: Pass | LGPL-3.0-or-later | |
| Journal Of Climatebrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.8k | Automated safety check: Pass | MIT | |
| scikit-survival Time-to-Event Modelingdavila7/claude-code-templates | 32k | 12 repos | ~3.7k | Automated safety check: Pass | MIT |
JCLiuGroup/AI-Computational-Chemist
Prepare, run, and validate LAMMPS molecular dynamics. An agent skill from JCLiuGroup/AI-Computational-Chemist.
majiayu000/claude-skill-registry
GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT.
jinzhezenggroup/computational-chemistry-agent-skills
Prepares, validates and runs DP-GEN simplify jobs that thin out repeated or redundant DeepMD datasets, generating param.json and machine.json for local or scheduler runs.
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when targeting Journal of Climate or deciding whether a climate-dynamics or climate-variability manuscript fits this venue.
davila7/claude-code-templates
Fits and evaluates survival models with scikit-survival: Cox models, Random Survival Forests, boosting, survival SVMs, concordance index, Brier score and competing risks.
K-Dense-AI/scientific-agent-skills
Analyzes Neuropixels extracellular recordings end-to-end with SpikeInterface.
Hello-QM/catgo-LRG
Drive a file-first, agent-in-the-loop computational campaign via a folder + markdown tree (no DB).
Hello-QM/catgo-LRG
Compute adsorption/reaction Gibbs free energies, free-energy diagrams, and electrochemical overpotentials (HER/ORR/OER/CO2RR/NRR) with VASP.
Hello-QM/catgo-LRG
Generate and manage ABINIT DFT calculations. An agent skill from Hello-QM/catgo-LRG.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks to place an adsorbate molecule on a surface, find adsorption sites, or set up a surface+adsorbate model for DFT.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks for adsorption energy, binding energy, or wants to compare how strongly a molecule binds to a surface.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks to analyze computational results: Gibbs free energy, OER/HER/CO2RR overpotentials, adsorption energy, convergence tests, DOS/d-band analysis, or Bader…
Categories
Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials. Lammps Deepmd is an agent skill from Hello-QM/catgo-LRG. Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials.
Lammps Deepmd fits situations like: the user wants MD simulations driven by a trained DP model; tasks that involve Physical and earth sciences; tasks that involve Machine learning.
Run `npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a claude-code`. Or copy the skill folder (.claude/skills/lammps-deepmd in Hello-QM/catgo-LRG) into .claude/skills/lammps-deepmd in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Hello-QM/catgo-LRG --skill lammps-deepmd -a codex`. Or copy the skill folder (.claude/skills/lammps-deepmd in Hello-QM/catgo-LRG) into .agents/skills/lammps-deepmd in your project. Codex loads it when a task matches its description.
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 lammps-deepmd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lammps-deepmd, .gemini/skills/lammps-deepmd, .github/skills/lammps-deepmd and .opencode/skills/lammps-deepmd in your project.
SKILL.md names no scripts, command-line tools or credentials: Lammps Deepmd is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): Requires LAMMPS compiled with the DEEPMD package. A frozen DeePMD model (.pb) is required. .
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.
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.
Lammps Deepmd 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.
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Lammps Deepmd: Lammps (JCLiuGroup/AI-Computational-Chemist, 145 stars), Optimize For GPU (majiayu000/claude-skill-registry, 666 stars), DP-GEN Simplify Workflow (jinzhezenggroup/computational-chemistry-agent-skills, 148 stars) and Journal Of Climate (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.