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Process-based discrete-event simulation. Model queues, shared resources, timed events: manufacturing, service ops, network traffic, logistics. Processes are Python generators yielding events. Resources: capacity-limited (Resource/Priority/Preemptive), bulk (Container), objects (Store, FilterStore). For continuous use SciPy ODEs; for agent-based use Mesa.

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.

Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, implementing generic classes, defining structural interfaces, or configuring mypy/pyright.

Um wrapper Pythonic para RDKit, oferecendo uma interface simplificada e padrões sensatos para tarefas padrão de descoberta de medicamentos, como análise de SMILES, padronização, descritores, impressões digitais, agrupamento, conformadores 3D e processamento paralelo. Ele retorna objetos nativos rdkit.Chem.Mol, sendo o uso direto do RDKit recomendado para controle avançado.

Biopython sequence analysis: parse FASTA/FASTQ/GenBank/GFF (SeqIO), NCBI Entrez (esearch/efetch/elink), remote/local BLAST, pairwise/MSA alignment (PairwiseAligner, MUSCLE/ClustalW), phylogenetic trees (Phylo). Use for gene family studies, phylogenomics, comparative genomics, NCBI pipelines. For PCR/restriction/cloning use biopython-molecular-biology; for SAM/BAM use pysam.

Fast Python environment management with uv (10-100x faster than pip). Triggers on: uv, venv, pip, pyproject, python environment, install package, dependencies.

Guia completo de desenvolvimento Firebase para aplicações hospedadas no GCP, abrangendo operações do Firestore, Cloud Functions, CLI, emuladores, regras de segurança, autenticação, hospedagem e integração com GCP.

Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variat

Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DNA, RNA, or protein sequences.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Python population genetics with scikit-allel. Read VCF files, compute allele frequencies, calculate diversity statistics, perform PCA, and run selection scans using GenotypeArray and HaplotypeArray data structures. Use when analyzing population genetics in Python.