lammps-workflow

lammps-workflow is a skill for Claude Code, Codex from SFETNI/Deep-Matter-Chem-Skills. It costs 5 tokens per session (8,414 once invoked), scanned A, original, MIT.

A guide for running molecular dynamics simulations in LAMMPS, an open-source program that models how atoms move and interact over time.

In plain words
What is it for?
Use it to set up, run, diagnose, or extend LAMMPS simulations for materials such as metals, polymers, and reactive systems.
Why use it?
It helps structure simulation setup and troubleshooting, including force-field choices, temperature control, equilibration, restarts, and parallel runs.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to set up, run, diagnose, or extend LAMMPS simulations for materials such as metals, polymers, and reactive systems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sfetni/deep-matter-chem-skills/lammps-workflow
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add SFETNI/Deep-Matter-Chem-Skills --skill lammps-workflow
Clone the repo
git clone --depth 1 https://github.com/SFETNI/Deep-Matter-Chem-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lammps-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/lammps-workflow/github.svg)](https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/lammps-workflow)
Your own site
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/lammps-workflow"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/lammps-workflow/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for lammps-workflow

Your own site · 80×15
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/lammps-workflow"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/lammps-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 5 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,414 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00005 $0.08414
Opus 5 $0.00003 $0.04207
Sonnet 5 $0.00001 $0.01683
Haiku 4.5 $0.00001 $0.00841

Measured 12d ago against content hash 4e37dd96f667, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

lammps-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/atomistic-md/lammps-workflow/SKILL.md · 521 lines

How it starts

The opening of the file, as written. The whole thing — 521 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LAMMPS Workflow

Description

This skill covers end-to-end molecular dynamics simulations using LAMMPS (Large-scale Atomic/Massively Parallel Simulator): input script anatomy, force-field selection and deployment, ensemble control, equilibration protocol, production runs, restart logic, and parallel execution. LAMMPS is the dominant open-source MD code for materials science applications and the standard deployment target for ML interatomic potentials. Invoke this skill when setting up, running, diagnosing, or extending a LAMMPS simulation of any material class from metals to polymers to reactive systems.

Domain Context

LAMMPS integrates Newton's equations of motion for a set of interacting particles under a chosen force field. The equations are solved numerically using a symplectic integrator (Velocity Verlet by default), which conserves a shadow Hamiltonian close to the true Hamiltonian and preserves time-reversibility. Key physical approximations:

  • Force field validity domain: Every pair_style encodes specific physical assumptions. EAM is validated for FCC metals near equilibrium; it fails for surfaces, defects with large distortions, or alloys outside the training composition range. Tersoff is validated for covalent semiconductors; it fails for amorphous structures far from the fitting database. ReaxFF can model bond breaking/forming but has known failures for unusual coordination environments. The force field, not the integrator, is the dominant source of error.
  • Classical vs. quantum nuclei: LAMMPS integrates classical equations of motion. Zero-point energy and nuclear quantum effects are neglected. This is a good approximation for heavy atoms (≥ C) above ~200 K, but fails for light atoms (H, He, Li) at low temperature and for tunneling-dominated processes. [EXPERT REVIEW NEEDED for precise crossover conditions]
  • Boundary conditions: LAMMPS supports periodic (p), shrink-wrapped (s), and fixed (f) boundaries. Periodic boundaries impose artificial periodicity; the simulation box must be large enough that a particle does not interact with its own image through the cutoff.
  • Timestep and numerical stability: The timestep must resolve the fastest vibrational frequency in the system. A rule of thumb is dt ≤ period / 20. For stiff bonds (O-H, C-H) in molecular force fields, this requires dt ≤ 0.5 fs or constrained bonds (SHAKE/RATTLE). For metals with EAM, 1–2 fs is typically safe. For ReaxFF with short-range repulsion, 0.1–0.5 fs is required. Exceeding the stability limit produces exponentially growing kinetic energy — the "energy explosion" failure mode.
  • Ergodicity and sampling: A single MD trajectory samples the microcanonical or canonical ensemble only if it is ergodic on the timescale of the run. Rare events (phase transitions, defect migration, folding) may not be sampled. Enhanced sampling methods are required for free energy calculations.

Read the full file on GitHub · 521 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 521 lines · 5 tokens per session scan A 4e37dd96f667

Subscribe to this mod's changes

lammps-workflow is a skill published in the GitHub repository SFETNI/Deep-Matter-Chem-Skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 5 tokens to every session and 8,414 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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