molecular-dynamics

molecular-dynamics is a skill for Claude Code, Codex from K-Dense-AI/scientific-agent-skills. It costs 67 tokens per session (3,614 once invoked), scanned A, original, MIT.

A set of tools for simulating how proteins, drug molecules, and other molecular systems move over time according to physics. OpenMM runs the simulations, while MDAnalysis reads and measures the resulting movement.

In plain words
What is it for?
Use it to set up protein or small-molecule systems, apply force fields, run energy minimisation and simulations, and analyse trajectories with measures such as RMSD, RMSF, contact maps, and free-energy surfaces.
Why use it?
It helps turn static molecular structures into time-based data, making it possible to study flexibility, stability, interactions, and binding behaviour computationally.

Skill for Claude CodeCodex

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

Good fit Use it to set up protein or small-molecule systems, apply force fields, run energy minimisation and simulations, and analyse trajectories with measures such as RMSD, RMSF, contact maps, and free-energy surfaces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/k-dense-ai/scientific-agent-skills/molecular-dynamics
About the project

Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.

K-Dense-AI/scientific-agent-skills · 44,220 stars · on GitHub · arxiv.org

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 K-Dense-AI/scientific-agent-skills --skill molecular-dynamics
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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 molecular-dynamics

README.md
[![agentmods](https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics/github.svg)](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics/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 molecular-dynamics

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/molecular-dynamics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,614 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. Third-party audits
  • Socket pass 9 Apr 2026
  • Snyk pass 9 Apr 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00067 $0.03614
Opus 5 $0.00034 $0.01807
Sonnet 5 $0.00013 $0.00723
Haiku 4.5 $0.00007 $0.00361

Measured 8d ago against content hash ca248ad20180, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

molecular-dynamics 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 8d 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.

Origin

Copies of this mod

6 near-identical copies found in the catalogue:

skills/molecular-dynamics/SKILL.md · 459 lines

How it starts

The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Molecular Dynamics

Overview

Molecular dynamics (MD) simulation computationally models the time evolution of molecular systems by integrating Newton's equations of motion. This skill covers two complementary tools:

  • OpenMM (https://openmm.org/): High-performance MD simulation engine with GPU support, Python API, and flexible force field support
  • MDAnalysis (https://mdanalysis.org/): Python library for reading, writing, and analyzing MD trajectories from all major simulation packages

Installation:

conda install -c conda-forge openmm mdanalysis nglview
# or
uv pip install openmm mdanalysis

When to Use This Skill

Use molecular dynamics when:

  • Protein stability analysis: How does a mutation affect protein dynamics?
  • Drug binding simulations: Characterize binding mode and residence time of a ligand
  • Conformational sampling: Explore protein flexibility and conformational changes
  • Protein-protein interaction: Model interface dynamics and binding energetics
  • RMSD/RMSF analysis: Quantify structural fluctuations from a reference structure
  • Free energy estimation: Compute binding free energy or conformational free energy
  • Membrane simulations: Model proteins in lipid bilayers
  • Intrinsically disordered proteins: Study IDR conformational ensembles

Core Workflow: OpenMM Simulation

1. System Preparation

from openmm.app import *
from openmm import *
from openmm.unit import *
import sys

def prepare_system_from_pdb(pdb_file, forcefield_name="amber14-all.xml",
                              water_model="amber14/tip3pfb.xml"):
    """
    Prepare an OpenMM system from a PDB file.

    Args:
        pdb_file: Path to cleaned PDB file (use PDBFixer for raw PDB files)
        forcefield_name: Force field XML file
        water_model: Water model XML file

    Returns:
        pdb, forcefield, system, topology
    """
    # Load PDB
    pdb = PDBFile(pdb_file)

    # Load force field
    forcefield = ForceField(forcefield_name, water_model)

    # Add hydrogens and solvate
    modeller = Modeller(pdb.topology, pdb.positions)
    modeller.addHydrogens(forcefield)

    # Add solvent box (10 Å padding, 150 mM NaCl)
    modeller.addSolvent(
        forcefield,
        model='tip3p',
        padding=10*angstroms,
        ionicStrength=0.15*molar
    )

    print(f"System: {modeller.topology.getNumAtoms()} atoms, "
          f"{modeller.topology.getNumResidues()} residues")

    # Create system
    system = forcefield.createSystem(
        modeller.topology,
        nonbondedMethod=PME,         # Particle Mesh Ewald for long-range electrostatics
        nonbondedCutoff=1.0*nanometer,
        constraints=HBonds,           # Constrain hydrogen bonds (allows 2 fs timestep)
        rigidWater=True,
        ewaldErrorTolerance=0.0005
    )

    return modeller, system

Read the full file on GitHub · 459 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 459 lines · 67 tokens per session scan A ca248ad20180

Subscribe to this mod's changes

molecular-dynamics is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,220 stars, last pushed 4d ago), licensed MIT. It adds 67 tokens to every session and 3,614 once invoked, about $0.0003 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 2026-09-03.

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