skills.homescapability registry অনুসন্ধান

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Science Comp.

Simulation and numerical analysis.

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scientific-computing

32

drugbank-database

Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill should be used when working with pharmaceutical data, drug discovery research, pharmacology studies, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task requiring detailed drug and drug target information from DrugBank.

lifangda

research

scientific-computing

32

hmdb-database

Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.

lifangda

research

scientific-computing

32

ethena-usde

"Synthetic dollar protocol with sUSDe staking yields, cooldown mechanics, and cross-chain balances."

jiayaoqijia

research

scientific-computing

32

md

Prepare ASE molecular-dynamics workflow tasks with backend-agnostic controls. Use when the user needs finite-temperature trajectories with explicit ensemble, timestep, thermostat, and output policies.

jinzhezenggroup

research

scientific-computing

32

dpgen-simplify

Prepare, explain, validate, and run DP-GEN simplify workflows for reducing repeated or redundant DeepMD datasets. Use when the user wants to generate or modify `param.json` and `machine.json`, run `dpgen simplify param.json machine.json`, organize repeated simplify experiments, or inspect simplify outputs.

jinzhezenggroup

research

scientific-computing

32

pymatgen-structure

Structure manipulation and crystal analysis workflows based on pymatgen. USE WHEN you need to read/write common atomistic formats (CIF, POSCAR, XYZ), build supercells, perform site substitution/doping, inspect symmetry (space group), or compute local structure descriptors for materials tasks.

jinzhezenggroup

research

scientific-computing

32

cobrapy

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

lifangda

research

scientific-computing

32

packmol-generate-mixture

A tool for generating initial packed molecular configurations (XYZ format) from single-molecule structures by calculating box dimensions, writing input scripts, and executing Packmol. USE WHEN you need to randomly pack a specific number of molecules into a simulation box (defined by target density or fixed lengths) to create starting geometries for molecular dynamics or related computational chemistry workflows.

jinzhezenggroup

research

scientific-computing

32

openbabel

A versatile CLI tool for converting molecular file formats, generating 3D atomic coordinates from SMILES, rendering 2D chemical structure images, and preparing or extracting structures for computational workflows. USE WHEN you need to convert between chemical file formats (e.g., xyz, pdb, mol, smi, gjf), generate 3D structures from SMILES using `--gen3d`, render molecule images (PNG/SVG), or extract geometries from simulation logs to build new inputs.

jinzhezenggroup

research

scientific-computing

32

dpdata-cli

A command-line utility for converting and manipulating over 50 atomic simulation data formats, including outputs from DFT and MD software (VASP, LAMMPS, Gaussian, QE, CP2K, ABACUS, etc.). USE WHEN you need to convert structural or trajectory files between different computational chemistry formats, or when parsing raw simulation outputs into structured training datasets (e.g., deepmd/raw, deepmd/npy, deepmd/hdf5) for DeePMD-kit.

jinzhezenggroup

research

scientific-computing

32

md

Prepare CP2K molecular-dynamics task inputs from a user-provided structure and MD controls. Use when the user needs finite-temperature trajectories with explicit ensemble, timestep, and thermostat/barostat settings.

jinzhezenggroup

research

scientific-computing

32

search-species

USE WHEN requesting core chemical structural data (SMILES, formula, mass, 2D images) via IUPAC, common, or multilingual names. You MUST actively retrieve the data using this skill; DO NOT hallucinate or generate structures yourself. DO NOT USE WHEN asking for physical properties (melting point, solubility), safety/toxicity data (MSDS), or synthesis pathways.

jinzhezenggroup

research

scientific-computing

32

rdkit-repr

A standardized CLI wrapper for RDKit molecular featurization workflows that handles physicochemical descriptor computation (outputs .csv) and molecular fingerprint extraction (outputs .npy or .csv), with built-in SMILES validation. USE WHEN you need to compute RDKit molecular descriptors or fingerprints from SMILES datasets (.csv/.smi), or when you want to list all available descriptor names and presets.

jinzhezenggroup

research

scientific-computing

31

bn-fit-modify

Guidance for Bayesian Network DAG structure recovery, parameter learning, and causal intervention tasks. This skill should be used when tasks involve recovering DAG structure from observational data, learning Bayesian Network parameters, performing causal interventions (do-calculus), or generating samples from modified networks. Applies to tasks mentioning Bayesian networks, DAG recovery, structure learning, causal inference, or interventional distributions.

letta-ai

research

scientific-computing

31

raman-fitting

This skill provides guidance for fitting peaks in Raman spectroscopy data, particularly for materials like graphene. Use this skill when tasks involve Raman spectrum analysis, peak fitting (G peak, 2D peak, D peak), or spectroscopic curve fitting using Lorentzian, Gaussian, or Voigt functions.

letta-ai

research

scientific-computing

31

raman-fitting

This skill provides guidance for Raman spectrum peak fitting tasks. It should be used when analyzing spectroscopic data, fitting Lorentzian or Gaussian peaks to Raman spectra, or working with graphene/carbon material characterization. The skill emphasizes critical data parsing verification, physical constraints from domain knowledge, and systematic debugging of curve fitting problems.

letta-ai

research

scientific-computing

31

tune-mjcf

This skill provides guidance for optimizing MuJoCo MJCF simulation files to improve performance while maintaining physics accuracy. Use this skill when tuning simulation parameters, reducing computation time, or balancing speed vs. accuracy trade-offs in MuJoCo models.

letta-ai

research

scientific-computing

31

distribution-search

Guidance for finding probability distributions that satisfy specific statistical constraints such as KL divergence targets. This skill should be used when tasks involve constructing probability distributions with exact numerical properties, optimization over high-dimensional probability spaces, or satisfying multiple simultaneous statistical constraints within tight tolerances.

letta-ai

research

scientific-computing

31

crack-7z-hash

This skill provides guidance for cracking 7z archive password hashes. It should be used when tasked with recovering passwords from 7z encrypted archives, extracting and cracking 7z hashes, or working with password-protected 7z files in CTF challenges, security testing, or authorized recovery scenarios.

letta-ai

research

scientific-computing

31

mcmc-sampling-stan

Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan modeling language, or running MCMC diagnostics. Applies to tasks involving posterior sampling, Bayesian inference, and probabilistic programming with Stan.

letta-ai

research

scientific-computing

31

crack-7z-hash

This skill provides guidance for cracking 7z archive password hashes. It should be used when tasks involve extracting hashes from password-protected 7z archives, selecting appropriate cracking tools, and recovering passwords through dictionary or brute-force attacks. Applicable to password recovery, security testing, and CTF challenges involving encrypted 7z files.

letta-ai

research

scientific-computing

31

adaptive-rejection-sampler

Guidance for implementing adaptive rejection sampling (ARS) algorithms for generating random samples from log-concave probability distributions. This skill should be used when tasks involve implementing ARS, rejection sampling, or Monte Carlo methods that require sampling from custom probability distributions, particularly in R or other statistical computing languages.

letta-ai

research

scientific-computing

31

password-recovery

Digital forensic skill for recovering passwords and sensitive data from disk images, deleted files, and binary data. This skill should be used when tasks involve extracting passwords from disk images, recovering deleted file contents, analyzing binary files for fragments, or forensic data recovery scenarios. Applies to tasks mentioning disk images, deleted files, password fragments, or data recovery.

letta-ai

research

scientific-computing

31

mcmc-sampling-stan

Guidance for Bayesian MCMC sampling tasks using RStan. This skill applies when implementing hierarchical Bayesian models, configuring Stan/RStan for MCMC inference, or working with posterior distributions. Use for tasks involving Stan model specification, RStan installation, MCMC diagnostics, and Bayesian hierarchical modeling.

letta-ai

research

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