अपने एजेंट के लिए सही क्षमता खोजें।
Molecular docking with AutoDock Vina via Python API. Receptor/ligand preparation (Meeko + RDKit), grid box setup, docking execution, pose extraction, binding energy analysis, and batch virtual screening. Use for protein-ligand docking and hit identification.
Query ChEMBL bioactive molecules and drug discovery data using the Python SDK. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki, EC50), find inhibitors for targets, perform SAR studies, and access drug mechanism/indication data for medicinal chemistry research.
pymatgen (Python Materials Genomics) is a materials science Python library for structure analysis, thermodynamics, and electronic property calculation. Parse and create crystal structures (CIF, POSCAR, CIF), query the Materials Project database for DFT-computed properties, analyze phase diagrams and pourbaix diagrams, compute X-ray diffraction patterns, and generate DFT input files for VASP, Quantum ESPRESSO, and CP2K. Alternatives: ASE (Atomic Simulation Environment) for MD/geometry; AFLOW for high-throughput; OVITO for visualization.
MaxQuant + Perseus proteomics pipeline: configure and run MaxQuant for label-free quantification (LFQ) and SILAC; parse proteinGroups.txt in Python; filter contaminants/reverse decoys; log2-transform and median-normalize LFQ intensities; impute MNAR missing values; t-test with FDR correction; volcano plot; GO/pathway enrichment. Use Proteome Discoverer for Thermo instrument-native processing; FragPipe/MSFragger for GPU-accelerated database search.
Computational molecular biology toolkit for sequence manipulation, file I/O (FASTA/GenBank/PDB), NCBI database access (Entrez), BLAST automation, pairwise/multiple sequence alignment, protein structure analysis (Bio.PDB), and phylogenetic tree construction. Use for batch sequence processing, custom bioinformatics pipelines, format conversion, and programmatic PubMed/GenBank queries. For quick gene lookups use gget; for multi-service REST APIs use bioservices.
Python library for analyzing molecular dynamics (MD) trajectories from GROMACS, AMBER, NAMD, CHARMM, and LAMMPS. Reads topology and trajectory files into Universe objects; supports RMSD, RMSF, radius of gyration, contact maps, hydrogen bond analysis, PCA, and custom distance/angle calculations across millions of frames. Use for structural analysis after MD simulations; use OpenMM or GROMACS directly for running simulations.
Pythonic wrapper around RDKit with simplified interface and sensible defaults for drug discovery cheminformatics. Use for SMILES parsing, molecular standardization, descriptor computation, fingerprints, similarity search, clustering, diversity selection, scaffold analysis, BRICS/RECAP fragmentation, 3D conformer generation, and molecular visualization. Returns native rdkit.Chem.Mol objects. Prefer datamol over raw RDKit for standard workflows; use RDKit directly for advanced control or custom parameters.
NeuroKit2 is a Python toolkit for neurophysiological signal processing. Process ECG (heart rate, HRV, R-peak detection), EEG (complexity, power spectral density), EMG (muscle activation onset), EDA/GSR (skin conductance, SCR decomposition), PPG (photoplethysmography), and RSP (respiration) signals. Simulate synthetic signals for testing. Alternatives: BioSPPy (older, less maintained), MNE (EEG/MEG specialist), heartpy (ECG only), scipy.signal (raw DSP without biosignal abstraction).
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Development standards for the Nathan n8n-Jira agent automation system. Covers n8n workflows, Python patterns, and project conventions.
Environment configuration and secrets management skill using UV for Python projects. Handles .env files, environment variables, secrets encryption, multi-environment setups, and secure configuration patterns. Use when setting up project environments, managing API keys, or implementing configuration best practices.
Expert guidance for creating and working with marimo notebooks - reactive Python notebooks that can be executed as scripts and deployed as apps. Use when the user asks to create marimo notebooks, convert Jupyter notebooks to marimo, build interactive dashboards or data apps with marimo, work with marimo's reactive programming model, debug marimo notebooks, or needs help with marimo-specific features (cells, UI elements, reactivity, SQL integration, deploying apps, etc.).
Generate high-quality, minimalistic, and geometric SVG logos using Python scripts. Use this skill when users need to create logos, icons, or visual identities with geometric primitives (circles, rects, paths) and specific color schemes. Applies generative design principles with standardized workflows for scalable SVG output.
Master Cohere v2 Chat API with Python, specializing in entity extraction using JSON Schema mode for structured outputs. Use when extracting entities from text, building data extraction pipelines, implementing NER systems, or requiring validated JSON responses from LLMs.
Creates bauplan data pipeline projects with SQL and Python models. Use when starting a new pipeline, defining DAG transformations, writing models, or setting up bauplan project structure from scratch.
Master SurrealDB 2.3.x with Python for multi-model database operations including CRUD, graph relationships, vector search, and real-time queries. Use when working with SurrealDB databases, implementing graph traversal, semantic search with embeddings, or building RAG applications.
Context management tools for Claude Code - provides intelligent codebase mapping with Python, Rust, and C++ parsing, duplicate detection, and MCP-powered symbol queries. Use this skill when working with large codebases that need automated indexing and context management.
Expert Unreal Engine 5 developer and technical artist for complete game development via agentic coding. Enables AI-driven control of Unreal Editor through MCP, Python scripting, Blueprints, and C++ for level design, asset management, gameplay programming, and visual development.
