mat-md-probability-density

mat-md-probability-density is a skill for Claude Code, Codex from learningmatter-mit/AtomisticSkills. It costs 26 tokens per session (865 once invoked), scanned A, original, MIT.

Calculate and visualize the probability density of diffusing ions from a Molecular Dynamics (MD) trajectory.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/learningmatter-mit/atomisticskills/mat-md-probability-density
Any agent
npx skills add learningmatter-mit/AtomisticSkills --skill mat-md-probability-density
Clone the repo
git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills

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 mat-md-probability-density

README.md
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Your own site
<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-md-probability-density"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-md-probability-density.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 865 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00026 $0.00865
Opus 5 $0.00013 $0.00432
Sonnet 5 $0.00005 $0.00173
Haiku 4.5 $0.00003 $0.00086

Measured today against content hash f6b05b04bd2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mat-md-probability-density 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 today.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/calculate_probability_density.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/mat-md-probability-density/SKILL.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MD Probability Density Visualization

Goal

To visualize the spatial probability density of mobile ions (e.g., Li, Na) from an MD simulation trajectory. This helps in understanding conduction pathways and identifying preferred occupation sites within the crystal structure. The output is a volumetric data object in CHGCAR format, which can be easily visualized using VESTA.

Instructions

  1. MD Simulation: Run an MD simulation at an appropriate temperature to observe sufficient diffusion events.

    Note: Short MD trajectories (e.g., ≤10 ps) often have too few discrete ion hops to naturally form continuous probability density tubes. The resulting density will look like isolated blobs exactly at the crystal lattice sites. To visualize continuous macroscopic diffusion pathways for short trajectories, use the --log compression flag to mathematically connect the sparse pathways.

    • The trajectory is typically saved to trajectory.traj.
    • Ensure supercell_min_length is reasonably large (>10 Å) to avoid finite-size artifacts in the density mapping.
    • Allow the simulation to run long enough so that the ions sample the entire available volume (e.g., 50-100 ps or more).
  2. Calculate Probability Density: Use the provided script to extract the fractional coordinates of the targeted species over time and convert them into a spatial density grid.

    # Env: base-agent
    python .agents/skills/mat-md-probability-density/scripts/calculate_probability_density.py \
        results/md_600K/trajectory.traj \
        --species Li \
        --interval 0.2 \
        --ignore_ps 5.0 \
        --output_chgcar results/md_600K/CHGCAR_proba
    
    • --species: The specific diffusing ion to visualize.
    • --interval: Grid spacing in Angstroms (0.1 to 0.5 is recommended). Smaller values give smoother isosurfaces but take longer to process and generate larger files. Defaults to 0.2 Å.
    • --ignore_ps: The equilibration time to discard from the beginning of the trajectory.
    • The script will automatically detect the frame time step if a .log file is available alongside the .traj file.

Read the full file on GitHub · 52 lines

Files

What ships with it

5 files 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. today First seen · 52 lines · 26 tokens per session scan A f6b05b04bd2d

Subscribe to this mod's changes

mat-md-probability-density is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 865 once invoked, about $0.0001 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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