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AI-powered shopping API for product search and crypto checkout. Use this skill when:\n- Searching for products from Amazon and Shopify\n- Building shopping assistants or product recommendation features\n- Creating purchase orders with crypto (USDC on Solana or Base)\n-

Commit and push vault changes to Git with smart commit messages. Auto-stages files, creates meaningful commits, and syncs with remote. Use after making vault changes or at end of day.

Runs all necessary checks (lint, tests) and pushes to GitHub. Use this as the final safety gate.

Create a new PR or push commits to an existing PR for the current branch.

Push Packer build metadata to HCP Packer registry for tracking and managing image lifecycle. Use when integrating Packer builds with HCP Packer for version control and governance.

Trade prediction markets on PvE. Access live OSINT feeds, Twitter signals, market data, and paper trade with virtual funds. Compete on the AI agent leaderboard.

Consulta y optimiza precios de electricidad PVPC en España (tarifa 2.0TD para usuarios domésticos). Usa cuando necesites (1) precio actual con contexto (alto/medio/bajo vs día), (2) identificar periodos valle/llano/punta según horario, (3) encontrar las horas más baratas del

Progressive Web Apps - service workers, caching strategies, offline, Workbox

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files,

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

Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best for complex workflows, multi-vendor setups, simulation. For Opentrons-only

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.

Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing.

Migrate a file to use stricter Pyrefly type checking with annotations required for all functions, classes, and attributes.

Python language server (Pyright) providing static type checking, code intelligence, and LSP diagnostics for .py and .pyi files. Use when working with Python code that needs type checking, autocomplete suggestions, error detection, or code navigation.

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

Analyze Python code quality using MCP tools - complexity, clones, dead code, coupling. Use when user asks about code quality, refactoring, maintainability, duplicates, or technical debt.

Pyspark Transformer - Auto-activating skill for Data Pipelines.\nTriggers on: pyspark transformer, pyspark transformer\nPart of the Data Pipelines skill category.

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

Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.

Generate pytest test generator operations. Auto-activating skill for Test Automation.\nTriggers on: pytest test generator, pytest test generator\nPart of the Test Automation skill category. Use when writing or running tests. Trigger with phrases like \

Python development with ruff, mypy, pytest - TDD and type safety

Common Python anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.

Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.

Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.

Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.

Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use when making architecture decisions, refactoring code structure, or evaluating when abstractions are appropriate.

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

Senior Python developer expertise for writing clean, efficient, and well-documented code.\nUse when: writing Python code, optimizing Python scripts, reviewing Python code for best practices,\ndebugging Python issues, implementing type hints, or when user mentions Python, PEP 8,

Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

Transform sequential Python code into parallel/concurrent implementations. Use when asked to parallelize Python code, improve code performance through concurrency, convert loops to parallel execution, or identify parallelization opportunities. Handles CPU-bound

Pythonic 惯用法、PEP 8 标准、类型提示以及构建健壮、高效、可维护的 Python 应用程序的最佳实践。

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Run and test Python code in a dedicated playground directory. Use when you need to execute Python scripts, test code snippets, investigate CPython behavior, or experiment with Python without affecting the main codebase.

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. Use PROACTIVELY for Python development, optimization, or advanced Python

Python project organization, module architecture, and public API design. Use when setting up new projects, organizing modules, defining public interfaces with __all__, or planning directory layouts.

Interactive Python REPL automation with common helpers and best practices

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state.

Guide for translating Python code to functional Scala style. Use when converting Python code involving higher-order functions, decorators, closures, generators, or when aiming for idiomatic functional Scala with pattern matching, Option handling, and monadic operations.

Guide for writing idiomatic Scala when translating from Python. Use when the goal is not just syntactic translation but producing clean, idiomatic Scala code. Covers immutability, expression-based style, sealed hierarchies, and common Scala conventions.

Guide for translating Python classes, inheritance, and object-oriented patterns to Scala. Use when converting Python code with classes, dataclasses, abstract classes, inheritance, properties, static methods, class methods, or design patterns.

Python SDK patterns for Opik. Use when working in sdks/python, on SDK APIs, integrations, or message processing.