Repository

learningmatter-mit/AtomisticSkills agent skills

Every skill in the learningmatter-mit/AtomisticSkills repository on GitHub, ranked by score, with the commands to install them.
skills
129
GitHub stars
176

GitHub description: “Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc)”

Stars
176 (29 forks)
Licence
MIT
Last push
Oct 2026
Created
Jan 2026

Install all skills

skills CLI (any agent)
npx skills add learningmatter-mit/AtomisticSkills

Add --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).

Skills in learningmatter-mit/AtomisticSkills, ranked

Ranked by score. Sort bymost stars,trending,newest,recently updated

Skills in learningmatter-mit/AtomisticSkills, ranked
#SkillRepositoryStarsUsed inTokensAuto-checkLicenceUpdated
1

Define a docking search box (center coordinates + box dimensions in Angstroms) from a co-crystal ligand, binding-site residues, or a saved JSON specification.

learningmatter-mit/AtomisticSkills176—~2.9kAutomated safety check: PassMITtoday
2

Build a solvated, charge-neutralized protein-ligand complex for OpenMM molecular dynamics simulation.

learningmatter-mit/AtomisticSkills176—~2kAutomated safety check: PassMITtoday
3

Identify and rank ligandable pockets on a protein structure or model using geometry (fpocket) or an ML predictor (P2Rank).

learningmatter-mit/AtomisticSkills176—~4kAutomated safety check: PassMITtoday
4

Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

learningmatter-mit/AtomisticSkills176—~2.5kAutomated safety check: PassMITtoday
5

Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITtoday
6

Query multiple MOF databases (QMOF via MPContribs; ARC-MOF DB7/Majumdar et al.

learningmatter-mit/AtomisticSkills176—~1.9kAutomated safety check: PassMITtoday
7

Query the Quantum MOF (QMOF) database via Materials Project's MPContribs platform for DFT-computed properties (bandgap) and optimized crystal structures of Metal-Organic Frameworks.

learningmatter-mit/AtomisticSkills176—~670Automated safety check: PassMITtoday
8

Search and download experimental InfraRed (IR), Mass spectra, and UV-Vis spectra data (JCAMP-DX format) for molecules.

learningmatter-mit/AtomisticSkills176—~529Automated safety check: PassMITtoday
9

Write and run custom ORCA input files for advanced electronic structure methods or settings not available through the SCINE wrapper, including multi-reference methods, excited states, relativistic…

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITtoday
10

Run DFT geometry optimization (minimization or TS search) on a molecular structure using ORCA via SCINE/ReaDuct wrapper.

learningmatter-mit/AtomisticSkills176—~2kAutomated safety check: PassMITtoday
11

Run a DFT or Coupled Cluster single-point energy calculation (with optional gradients/Hessian) on a molecular structure with ORCA through SCINE wrapper.

learningmatter-mit/AtomisticSkills176—~1.8kAutomated safety check: PassMITtoday
12

Dock small-molecule guests into a porous host material using the VOID library (Voronoi Clustering), generating multiple 3D conformers with RDKit and ranking generated complexes.

learningmatter-mit/AtomisticSkills176—~918Automated safety check: PassMITtoday
13

Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.

learningmatter-mit/AtomisticSkills176—~702Automated safety check: PassMITtoday
14

Verify non-periodic molecular TS connectivity with forward/reverse IRC using endpoint connectivity and RMSD checks.

learningmatter-mit/AtomisticSkills176—~972Automated safety check: PassMITtoday
15

Predict LC-MS/MS (MS2, tandem mass spectra) from SMILES via ICEBERG, a two-stage deep neural network.

learningmatter-mit/AtomisticSkills176—~1.6kAutomated safety check: PassMITtoday
16

Calculate activation barrier using Nudged Elastic Band (NEB) method with MLIPs.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITtoday
17

Scripts for Wasserstein deconvolution of 1H NMR mixture spectra against reference spectra, reaction product prediction, time-series kinetics, and spectral plotting.

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITtoday
18

Predict 1H NMR spectra from SMILES strings via NMRdb.org SPINUS neural network prediction and nmrsim quantum mechanical spin simulation.

learningmatter-mit/AtomisticSkills176—~1.8kAutomated safety check: PassMITtoday
19

Generate transition state structures for chemical reactions using React-OT.

learningmatter-mit/AtomisticSkills176—~914Automated safety check: PassMITtoday
20

Find structurally similar chemical compounds using PubChem's 2D fast similarity engine via the PUG-REST API.

learningmatter-mit/AtomisticSkills176—~614Automated safety check: PassMITtoday
21

Set up and run molecular dynamics simulations of molecules in explicit solvent boxes using Packmol for box construction and MLIPs for dynamics.

learningmatter-mit/AtomisticSkills176—~1.9kAutomated safety check: PassMITtoday
22

Calculates gas adsorption isotherms via BVT/GCMC Monte Carlo simulations in a porous framework using MLIP.

learningmatter-mit/AtomisticSkills176—~926Automated safety check: PassMITtoday
23

Prepares supercells for porous frameworks based on minimum interplanar distance and relaxes them using standard MLIP relaxation tools.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITtoday
24

Calculates Henry coefficient and heat of adsorption for a gas in a porous framework using Widom insertion with any supported MLIP.

learningmatter-mit/AtomisticSkills176—~853Automated safety check: PassMITtoday
25

Match an experimental spectrum (1H NMR, 13C NMR, IR) against predicted or database reference spectra for candidate ranking and structure confirmation.

learningmatter-mit/AtomisticSkills176—~2.5kAutomated safety check: PassMITtoday
26

Compute gas-phase thermodynamic quantities (H, S, G) and reaction thermochemistry (ΔH, ΔS, ΔG) using MLIPs with the ideal-gas/rigid-rotor/harmonic-oscillator approximation.

learningmatter-mit/AtomisticSkills176—~1.4kAutomated safety check: PassMITtoday
27

Optimize non-periodic molecular TS guesses and verify first-order saddle point from vibrational modes.

learningmatter-mit/AtomisticSkills176—~876Automated safety check: PassMITtoday
28

Calculate vibrational frequencies, normal modes, zero-point energy, and IR spectra of molecules and clusters using MLIPs.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITtoday
29

Fetch biological assays and target proteins a chemical has been tested against via PubChem.

learningmatter-mit/AtomisticSkills176—~693Automated safety check: PassMITtoday
30

Query ChEMBL web services for targets, molecules, and curated bioactivity measurements (IC50, Ki, EC50, etc.).

learningmatter-mit/AtomisticSkills176—~1.4kAutomated safety check: PassMITtoday
31

Search, filter, and retrieve macromolecular structures from the RCSB Protein Data Bank (PDB), including metadata, bound ligands, and optional coordinate/validation downloads.

learningmatter-mit/AtomisticSkills176—~1.1kAutomated safety check: PassMITtoday
32

Query PubChem via PUG-REST to retrieve CIDs, computed properties, synonyms, and 2D/3D SDF structures.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITtoday
33

Post-docking analysis of virtual screening results including score distributions, enrichment metrics (ROC AUC, enrichment factors), and ligand efficiency calculations.

learningmatter-mit/AtomisticSkills176—~2.2kAutomated safety check: PassMITtoday
34

Dock small-molecule ligands into a protein receptor using AutoDock Vina (Python API) and save ranked poses + docking metadata for reproducible virtual screening.

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITtoday
35

Prepare small-molecule ligands for docking and analysis via optional state enumeration, 3D conformer generation, MMFF/UFF minimization, and export to SDF + AutoDock PDBQT.

learningmatter-mit/AtomisticSkills176—~772Automated safety check: PassMITtoday
36

Compute single-trajectory MM-GBSA and / or MM-PBSA binding free energy estimates from a protein-ligand MD trajectory.

learningmatter-mit/AtomisticSkills176—~4.7kAutomated safety check: PassMITtoday
37

Validate docked or generated ligand poses for physical plausibility using PoseBusters, filtering out chemically invalid or clashing poses before downstream refinement.

learningmatter-mit/AtomisticSkills176—~1.3kAutomated safety check: PassMITtoday
38

Run a protein-ligand MD simulation in OpenMM with energy minimization, restrained equilibration, and production NPT, producing trajectory and checkpoint files for downstream analysis.

learningmatter-mit/AtomisticSkills176—~1.4kAutomated safety check: PassMITtoday
39

Prepare macromolecular receptor structures (PDB/mmCIF or RCSB PDB ID) for docking or simulation by fixing common structure issues and adding hydrogens.

learningmatter-mit/AtomisticSkills176—~1.1kAutomated safety check: PassMITtoday
40

Compute symmetry-corrected heavy-atom RMSD between docked poses and a reference crystal ligand to validate docking protocols.

learningmatter-mit/AtomisticSkills176—~2.3kAutomated safety check: PassMITtoday
41

Predict synthetic accessibility and retrosynthetic pathways for novel molecules using the IBM RXN API.

learningmatter-mit/AtomisticSkills176—~647Automated safety check: PassMITtoday
42

Analyze a protein-ligand MD trajectory to compute ligand RMSD, pocket RMSF, hydrogen bonds, contact occupancy, and protein-ligand interaction fingerprints over time.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: PassMITtoday
43

Search and retrieve research papers from ArXiv API for scientific research.

learningmatter-mit/AtomisticSkills176—~634Automated safety check: PassMITtoday
44

Set up, check or troubleshoot how AtomisticSkills runs on this machine -- creating its Python environments, connecting its MCP servers, choosing uv or a container runtime, and configuring API keys.

learningmatter-mit/AtomisticSkills176—~1.2kAutomated safety check: NotesMITtoday
45

Search and retrieve preprint metadata from bioRxiv and medRxiv APIs for biological and medical research.

learningmatter-mit/AtomisticSkills176—~854Automated safety check: PassMITtoday
46

Retrieve extensive literature (PubMed) and patent associated with a specific chemical compound via PubChem.

learningmatter-mit/AtomisticSkills176—~515Automated safety check: PassMITtoday
47

Retrieves averaged elemental prices and provides direct vendor purchase links for elements and precursor compounds.

learningmatter-mit/AtomisticSkills176—~566Automated safety check: PassMITtoday
48

Search for patents by keyword, material name, or assignee using free data sources (Google Patents).

learningmatter-mit/AtomisticSkills176—~540Automated safety check: PassMITtoday

Questions, answered from the data.

What is the best skill in learningmatter-mit/AtomisticSkills?

Drug Binding Site Definition from learningmatter-mit/AtomisticSkills ranks first of the 129 skills in learningmatter-mit/AtomisticSkills listed here, with the highest score: its repository has 176 GitHub stars, its SKILL.md loads about 2.9k tokens and it passes the automated safety check with no findings. Next come Drug Complex System Builder and Drug Pocket Detection.

Are the skills in learningmatter-mit/AtomisticSkills official?

None yet. All 129 skills in learningmatter-mit/AtomisticSkills listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.

How do I install all skills from learningmatter-mit/AtomisticSkills?

Run npx skills add learningmatter-mit/AtomisticSkills in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.

How are these skills ranked?

By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.