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.
npx skills add tondevrel/scientific-agent-skills --skill mdanalysisgit clone --depth 1 https://github.com/tondevrel/scientific-agent-skillsWrote 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.
[](https://agentmods.dev/skills/tondevrel/scientific-agent-skills/mdanalysis)<a href="https://agentmods.dev/skills/tondevrel/scientific-agent-skills/mdanalysis"><img src="https://agentmods.dev/badge/skills/tondevrel/scientific-agent-skills/mdanalysis.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.14968 |
| Opus 5 | $0.00035 | $0.07484 |
| Sonnet 5 | $0.00014 | $0.02994 |
| Haiku 4.5 | $0.00007 | $0.01497 |
Grade A, and why
mdanalysis 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.
How it starts
The opening of the file, as written. The whole thing — 1,922 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MDAnalysis - Molecular Dynamics Analysis
Python library for reading, writing, and analyzing molecular dynamics trajectories and structural files.
When to Use
- Loading MD trajectories (DCD, XTC, TRR, NetCDF, etc.)
- RMSD and RMSF calculations
- Distance, angle, and dihedral analysis
- Atom selections (VMD-like syntax)
- Hydrogen bond analysis
- Solvent Accessible Surface Area (SASA)
- Protein secondary structure analysis
- Membrane system analysis
- Water/ion distribution analysis
- Trajectory alignment and fitting
- Custom trajectory analysis
- Converting between file formats
Reference Documentation
Official docs: https://www.mdanalysis.org/docs/
Search patterns: MDAnalysis.Universe, MDAnalysis.analysis.rms, MDAnalysis.analysis.distances
Core Principles
Use MDAnalysis For
| Task | Module | Example |
|---|---|---|
| Load trajectory | Universe |
Universe(topology, trajectory) |
| RMSD calculation | analysis.rms |
RMSD(mobile, ref) |
| Atom selection | select_atoms |
u.select_atoms('protein') |
| Distance analysis | analysis.distances |
distance_array(pos1, pos2) |
| H-bond analysis | analysis.hbonds |
HydrogenBondAnalysis() |
| SASA calculation | analysis.sasa |
SASAnalysis() |
| Contacts analysis | analysis.contacts |
Contacts() |
| Trajectory writing | Writer |
with Writer() as W |
Do NOT Use For
- Running MD simulations (use GROMACS, AMBER, NAMD)
- Force field calculations (use OpenMM, MDTraj)
- Quantum chemistry (use PySCF, Qiskit)
- Protein structure prediction (use AlphaFold, RosettaFold)
- Initial structure building (use Biopython, PyMOL)
Quick Reference
Installation
# pip
pip install MDAnalysis
# With additional analysis modules
pip install MDAnalysis[analysis]
# conda
conda install -c conda-forge mdanalysis
# Development version
pip install git+https://github.com/MDAnalysis/mdanalysis.git
Standard Imports
# Core imports
import MDAnalysis as mda
from MDAnalysis import Universe
from MDAnalysis.analysis import rms, align, distances
# Common analysis modules
from MDAnalysis.analysis.rms import RMSD, RMSF
from MDAnalysis.analysis.distances import distance_array
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis
from MDAnalysis.analysis.dihedrals import Dihedral
# Utilities
import numpy as np
import matplotlib.pyplot as plt
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.
- 8d ago First seen · 1,922 lines · 70 tokens per session scan A 3ab827cecd13
mdanalysis is a skill published in the GitHub repository tondevrel/scientific-agent-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 70 tokens to every session and 14,968 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 2026-08-30.
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