Skills directory · page 55

Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).

Laboratory automation toolkit for controlling liquid handlers, plate readers, pumps, heater shakers, incubators, centrifuges, and analytical equipment. Use this skill when automating laboratory workflows, programming liquid handling robots (Hamilton STAR, Opentrons OT-2, Tecan EVO), integrating lab equipment, managing deck layouts and resources (plates, tips, containers), reading plates, or creating reproducible laboratory protocols. Applicable for both simulated protocols and physical hardware control.

Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.

Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

Runs the PyPI release runbook — build, twine check, version bump, tag, upload. Use when the user wants a Python package published. Not for project scaffolding.

Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.

Scaffolds or retrofits a Python project with uv, ruff, strict mypy and a standard Makefile. Use when the user sets up Python tooling. Not for publishing.

Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.

Pythonic イディオム、PEP 8標準、型ヒント、堅牢で効率的かつ保守可能なPythonアプリケーションを構築するためのベストプラクティス。

Patrones idiomáticos de Python, estándares PEP 8, type hints y buenas prácticas para construir aplicaciones Python robustas, eficientes y mantenibles.

Python-specific design patterns and best practices including protocols, dataclasses, context managers, decorators, async/await, type hints, and package organization. Use when working with Python code to apply Pythonic patterns.

Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications. Use when writing or reviewing Python code and idiomatic structure, typing, or PEP 8 is in question.

Pythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar.

Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI.

Python testing best practices using pytest including fixtures, parametrization, mocking, coverage analysis, async testing, and test organization. Use when writing or improving Python tests.

Estrategias de pruebas Python usando pytest, metodología TDD, fixtures, mocking, parametrización y requisitos de cobertura.

Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements. Use when writing pytest tests — fixtures, mocks, parametrization, or coverage.

pytest, TDD metodolojisi, fixture'lar, mocking, parametrizasyon ve coverage gereksinimleri kullanarak Python test stratejileri.

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.

Produce QA acceptance criteria and a manual validation plan for a feature change — golden path, edge cases, error states, performance limits, and explicit pass/fail evidence.

Generate comprehensive test plans, manual test cases, regression test suites, and bug reports for QA engineers. Includes Figma MCP integration for design validation.

Comprehensive quantum computing toolkit for building, optimizing, and executing quantum circuits. Use when working with quantum algorithms, simulations, or quantum hardware including (1) Building quantum circuits with gates and measurements, (2) Running quantum algorithms (VQE, QAOA, Grover), (3) Transpiling/optimizing circuits for hardware, (4) Executing on IBM Quantum or other providers, (5) Quantum chemistry and materials science, (6) Quantum machine learning, (7) Visualizing circuits and results, or (8) Any quantum computing development task.

Use for ISO 13485 internal audits: planning the program, running an audit, classifying findings or preparing for an external audit. Optimizes the schedule with audit_schedule_optimizer.py.

Senior QMS Audit Expert for internal and external quality management system auditing. Provides ISO 13485 audit expertise, audit program management, nonconformity identification, and corrective action verification. Use for internal audit planning, external audit preparation, audit execution, and audit follow-up activities.

マージ前に必ず実行。静的チェック・テスト・体制レビュー（変更内容で決まる統合レビュアー＋反証型QA＋専門家最大1体、最大2巡で高の指摘だけを直して確かめる）と追加テスト（test-recommendation）を実施し、通過後のみmainへのマージ・直接pushが可能。指示に「スピード優先」とあれば、レビューと追加テストの実行を後回しの Issue にする。

Use for QMS document control: numbering, versioning, change control or 21 CFR Part 11 e-signatures. Validates documents with document_validator.py and tracks versions with document_version_control.py.

Senior Quality Documentation Manager for comprehensive documentation control and regulatory document review. Provides document management system design, change control, configuration management, and regulatory documentation oversight. Use for document control system implementation, regulatory document review, change management, and documentation compliance verification.

Use for QMR duties under ISO 13485 5.5.2: management review, quality policy and objectives, quality KPIs and cost of quality. Tracks reviews with management_review_tracker.py and monitors effectiveness with quality_effectiveness_monitor.py.

Senior Quality Manager Responsible Person (QMR) for HealthTech and MedTech companies. Provides overall quality system responsibility, regulatory compliance oversight, management accountability, and strategic quality leadership. Use for quality system governance, regulatory compliance oversight, management responsibility, and quality strategic planning.

ISO 13485 Quality Management System specialist for medical device companies. Provides QMS implementation, maintenance, process optimization, and compliance expertise. Use for QMS design, documentation control, management review, internal auditing, corrective actions, and ISO 13485 certification activities.

Build or maintain an ISO 13485 medical device QMS: design, documentation, CAPA, audit prep. Use whenever the user faces a 13485 certification audit or needs quality procedures.

Codified expertise in quality control, nonconformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Based on insights from quality engineers with 15+ years of experience in FDA, IATF 16949, and AS9100 environments. Includes nonconformance report lifecycle management, corrective and preventive action systems, statistical process control interpretation, and audit methods. Use when investigating nonconformances, conducting root cause analysis, managing corrective and preventive actions, interpreting statistical process control data, or handling supplier quality issues.

Quality control and non-conformance management for regulated manufacturing (FDA 21 CFR 820, IATF 16949, AS9100): NCR lifecycle and disposition, 5-Why/Ishikawa/fault-tree/8D root cause analysis, CAPA systems, SPC interpretation, AQL sampling, and supplier quality audits. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.

Patrones de arquitectura Quarkus 3.x LTS con Camel para mensajería, diseño de API RESTful, servicios CDI, acceso a datos con Panache y procesamiento asíncrono.

Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures.

Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures. Use when building or reviewing a Quarkus service, especially with Camel messaging or Panache data access.

Quarkus Security best practices for authentication, authorization, JWT/OIDC, RBAC, input validation, CSRF, secrets management, and dependency security.

Quarkus security implementation patterns: JWT and OIDC authentication, @RolesAllowed RBAC and SecurityIdentity checks, Bean Validation and custom validators, parameterized Panache queries, BCrypt password hashing, CORS and security headers, rate limiting, audit logging, Vault or environment-variable secrets, and dependency CVE scanning. Use when adding authentication or authorization, validating input, managing secrets, or hardening a Quarkus application.

Quarkus認証、認可、JWT/OIDC、RBAC、入力検証、CSRF、シークレット管理、依存関係セキュリティのセキュリティベストプラクティス。

Buenas prácticas de seguridad en Quarkus para autenticación, autorización, JWT/OIDC, RBAC, validación de entrada, CSRF, gestión de secretos y seguridad de dependencias.

Desarrollo guiado por pruebas para Quarkus 3.x LTS usando JUnit 5, Mockito, REST Assured, pruebas Camel y JaCoCo. Usar al agregar funcionalidades, corregir bugs o refactorizar servicios orientados a eventos.

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.