productivity▌

Streamlined PyTorch training framework with automatic distributed training, callbacks, and minimal boilerplate. \n \n Organizes PyTorch code into LightningModule with training_step, validation_step, and test_step methods; Trainer class handles device management, mixed precision, checkpointing, and logging automatically \n Supports distributed training strategies including DDP, FSDP, and DeepSpeed with single-line configuration; scales from laptop to multi-node clusters without code changes \n Bu

Event-Driven Architecture patterns for Spring Boot using domain events, transactional listeners, and Kafka messaging. \n \n Covers domain event design, ApplicationEventPublisher integration, and @TransactionalEventListener configuration for local event handling with AFTER_COMMIT phase guarantees \n Supports distributed messaging via Kafka and Spring Cloud Stream for inter-service communication with functional consumer beans \n Implements the transactional outbox pattern for reliable event publis

Comprehensive guide for creating modular skills that extend Codex's capabilities with specialized knowledge and workflows. \n \n Skills consist of a required SKILL.md file with YAML frontmatter (name, description) and optional bundled resources (scripts, references, assets) organized to manage context efficiently \n Follow a six-step creation process: understand concrete usage examples, plan reusable contents, initialize with init_skill.py, edit SKILL.md and resources, package with package_skill

You are a dependency management expert specializing in safe, incremental upgrades of project dependencies. Plan and execute dependency updates with minimal risk, proper testing, and clear migration paths for breaking changes.

GraphQL schema design, resolver patterns, and production safety best practices. \n \n Covers nine core capabilities including schema design, resolvers, federation, subscriptions, DataLoader, code generation, and Apollo tooling for both server and client \n Emphasizes critical production hazards: N+1 query problems, unlimited query depth leading to DoS, introspection exposure, and improper authorization scoping \n Provides patterns for type-safe schemas with intentional nullability, batch query o

Complete Python backtesting environment setup with OS detection, virtual environment, dependencies, and configuration. \n \n Detects operating system (macOS, Linux, Windows) and installs TA-Lib system dependencies accordingly \n Creates isolated Python virtual environment with pip upgrade and installs 15+ packages including vectorbt, openalgo, plotly, ta-lib, duckdb, and quantstats \n Prompts user to select market data source (Indian Markets via OpenAlgo or DuckDB, US Markets via yfinance, or Cr

$22

X/Twitter URL에서 트윗 원문, 작성자 정보, 인게이지먼트 데이터를 가져오는 스킬. FxEmbed 오픈소스 프로젝트의 API (api.fxtwitter.com)를 활용하여 JavaScript 없이 트윗 데이터를 추출한다.

Control home automation accessories and commission Matter devices. HomeKit manages the home/room/accessory model, action sets, and triggers. MatterSupport handles device commissioning into your ecosystem. Targets Swift 6.2 / iOS 26+.

Comprehensive skill for automating Jira project management and agile workflows.