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 agentmods add skills/kdevos12/alkyl/mdanalysisnpx skills add Kdevos12/ALKYL --skill mdanalysisgit clone --depth 1 https://github.com/Kdevos12/ALKYLWhat 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 | $0.00049 | $0.01026 |
| Opus 5 | $0.00024 | $0.00513 |
| Sonnet 5 | $0.00010 | $0.00205 |
| Haiku 4.5 | $0.00005 | $0.00103 |
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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MDAnalysis — MD Trajectory Analysis
MDAnalysis 2.10.0 (2025). Core pattern: Universe (topology + trajectory) → AtomGroup (selection) → AnalysisBase.run() → .results.
When to Use This Skill
- Loading GROMACS, AMBER, NAMD, CHARMM, LAMMPS trajectories
- RMSD and RMSF calculations (protein stability, flexibility)
- Structural alignment across trajectory frames
- Hydrogen bond detection and lifetime analysis
- Protein-ligand contacts and binding site analysis
- Dihedral angles (Ramachandran plots, chi angles)
- Secondary structure (DSSP) assignment
- PCA of conformational dynamics
- Radial distribution functions (RDF), density maps
- Mean square displacement (MSD), diffusion coefficients
Quick Start
import MDAnalysis as mda
from MDAnalysis.analysis import rms, align
# Load topology + trajectory
u = mda.Universe('protein.prmtop', 'traj.dcd')
print(u) # <Universe with 45000 atoms>
print(len(u.trajectory)) # number of frames
# Select atoms
protein = u.select_atoms('protein')
ca = u.select_atoms('protein and name CA')
ligand = u.select_atoms('resname LIG')
# Iterate trajectory
for ts in u.trajectory:
print(ts.frame, ts.time, ca.positions.mean(axis=0))
Router — What to Read
| Task | Reference |
|---|---|
| Universe, topology formats, selections, trajectory I/O, writing | references/universe-selections.md |
| RMSD, RMSF, alignment, radius of gyration | references/rmsd-rmsf-alignment.md |
| Hydrogen bonds, native contacts, binding residues | references/contacts-hbonds.md |
| Dihedrals, DSSP, PCA, RDF, density, MSD | references/structure-dynamics.md |
| Protein-ligand interaction analysis workflow | references/protein-ligand.md |
Key Modules
| Module | Import | Role |
|---|---|---|
rms |
from MDAnalysis.analysis import rms |
RMSD, RMSF |
align |
from MDAnalysis.analysis import align |
Structural alignment |
contacts |
from MDAnalysis.analysis import contacts |
Native contacts |
hydrogenbonds |
from MDAnalysis.analysis.hydrogenbonds.hbond_analysis import HydrogenBondAnalysis |
H-bonds |
dihedrals |
from MDAnalysis.analysis.dihedrals import Ramachandran, Janin |
Dihedral angles |
dssp |
from MDAnalysis.analysis.dssp import DSSP |
Secondary structure |
pca |
from MDAnalysis.analysis.pca import PCA |
Conformational PCA |
rdf |
from MDAnalysis.analysis.rdf import InterRDF |
Radial distribution |
density |
from MDAnalysis.analysis.density import DensityAnalysis |
Density maps |
msd |
from MDAnalysis.analysis.msd import EinsteinMSD |
Diffusion |
distances |
from MDAnalysis.analysis.distances import dist, between |
Distances |
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.
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.
- 2d ago First seen · 102 lines · 49 tokens per session scan A f6097ecf620d
mdanalysis is a skill published in the GitHub repository Kdevos12/ALKYL (6 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 1,026 once invoked, about $0.0002 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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