enhanced-sampling

enhanced-sampling is a skill for Claude Code, Codex from SFETNI/Deep-Matter-Chem-Skills. It costs 4 tokens per session (15,359 once invoked), scanned A, original, MIT.

A set of methods for atomistic molecular-dynamics simulations, which model how atoms move over time, when important changes are rare or slow.

In plain words
What is it for?
Use it to choose and test collective variables, run umbrella sampling or metadynamics, reconstruct free-energy surfaces, check convergence, and connect simulations with PLUMED and common simulation engines.
Why use it?
Standard simulation may not observe rare events, such as protein folding or ion movement, within the available time.

Skill for Claude CodeCodex

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

Good fit Use it to choose and test collective variables, run umbrella sampling or metadynamics, reconstruct free-energy surfaces, check convergence, and connect simulations with PLUMED and common simulation engines.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/enhanced-sampling/github.svg)](https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/enhanced-sampling)
Your own site
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/enhanced-sampling"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/enhanced-sampling/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 enhanced-sampling

Your own site · 80×15
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/enhanced-sampling"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/enhanced-sampling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 4 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 15,359 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00004 $0.15359
Opus 5 $0.00002 $0.07680
Sonnet 5 $0.00001 $0.03072
Haiku 4.5 $0.00000 $0.01536

Measured 11d ago against content hash a7c64df01181, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

enhanced-sampling scanned grade A with 1 finding 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 11d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run([
skills/atomistic-md/enhanced-sampling/SKILL.md · 991 lines

How it starts

The opening of the file, as written. The whole thing — 991 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Enhanced Sampling

Description

This skill covers enhanced sampling methods for atomistic MD simulations where rare events, large free-energy barriers, or slow conformational transitions prevent standard MD from converging on accessible timescales. It addresses collective variable (CV) selection and validation; umbrella sampling with WHAM/MBAR reconstruction; well-tempered metadynamics; adaptive biasing force; steered MD; temperature replica exchange; accelerated MD; free-energy surface convergence diagnostics; and PLUMED integration with GROMACS, LAMMPS, and ML interatomic potentials. Invoke this skill whenever a process of interest has an estimated barrier ≳ 10 k_B T or an estimated timescale that cannot be sampled directly within the available simulation budget.

Domain Context

Standard MD is limited to continuous trajectories. For a system at 300 K, barrier-crossing events with ΔG‡ ≳ 10 k_B T (≳ 25 kJ/mol) occur with rates of order k ~ ν exp(−ΔG‡/k_B T) ≈ 10¹³ × e⁻¹⁰ s⁻¹ ≈ 10⁻⁸ s⁻¹ — a mean first-passage time of ~100 ns. Protein folding, crystal nucleation, ion permeation through channels, and solid-state diffusion all fall into this regime.

Enhanced sampling methods modify the system to accelerate barrier crossing and then reconstruct the unbiased free energy surface (FES) from the biased simulation. The modifications take four forms:

  1. Bias potentials on collective variables (CVs): A time-varying or history-dependent potential V_bias(ξ) is added along one or more CVs ξ(r). The CV must capture the reaction coordinate — it must separate the metastable states and project out the slow degrees of freedom. A poor CV does not accelerate the relevant transition even if the method runs correctly.
  2. Hamiltonian or temperature ladders (replica exchange): Multiple copies of the system run in parallel at different temperatures or with different Hamiltonians. Exchanges between replicas are accepted with the Metropolis criterion, enabling high-temperature configurations to escape local minima and donate configurations to lower-temperature replicas.
  3. Time-independent bias (flat histogram): The WAN to-WHAM or MBAR approach reconstructs the FES from multiple biased simulations (umbrella sampling windows) by reweighting each frame by the inverse of its bias weight.
  4. Velocity-boosted or modified-potential approaches (accelerated MD): A dihedral or total boost potential is added to reduce barriers globally rather than along a specific CV.

Read the full file on GitHub · 991 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. 11d ago First seen · 991 lines · 4 tokens per session scan A a7c64df01181

Subscribe to this mod's changes

enhanced-sampling is a skill published in the GitHub repository SFETNI/Deep-Matter-Chem-Skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 4 tokens to every session and 15,359 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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