Skill UI

Execute end-to-end automated testing for mobile applications across both iOS and Android platforms. This skill simulates real user interactions, covering UI flows, gestures (swipe, pinch), form validation, and platform-specific behaviors (e.g., Safe Area handling, Android back button logic). It supports industry-standard frameworks like Appium, Detox, and Maestro, making it essential for ensuring cross-platform quality assurance and robust CI/CD pipelines.

This skill provides comprehensive guidance for the entire lifecycle of Conductor tracks—the logical work units used to organize features, bugs, and refactors. It assists users in creating, reviewing, updating specifications (spec.md), developing plans (plan.md), and managing the status and metadata of tasks from initial conception through final completion, ensuring structured and traceable development processes.

This skill provides production-grade patterns for Unity's Data-Oriented Technology Stack (DOTS). It covers essential components like Entity Component System (ECS), the Job System, and the Burst Compiler, enabling developers to build high-performance, scalable games. Use this when optimizing CPU-bound logic, managing thousands of entities, or migrating traditional OOP game code to a data-oriented design.

This skill provides robust strategies and Python implementations for dealing with API rate limiting (HTTP 429 errors) when interacting with services like Vast.ai. It includes automatic retry logic, exponential backoff algorithms, and optimized techniques for batch operations and polling, ensuring stable and efficient API throughput.

This guide provides comprehensive solutions for handling Vercel API rate limits (HTTP 429 errors). It covers implementing robust retry logic with exponential backoff for consuming Vercel's outbound APIs. Furthermore, it demonstrates how to configure Vercel's WAF rate limiting and custom edge configurations to protect your own deployed API endpoints, ensuring stability and preventing service abuse.

A comprehensive, production-ready TypeScript wrapper for interacting with the Vercel REST API. This client provides typed methods for managing deployments, projects, environment variables, and domains. It includes robust features like standardized error handling, exponential backoff retry logic, and structured request patterns, making programmatic integration with Vercel reliable and type-safe.

This skill functions as a documentation architect, capable of generating highly structured wiki catalogues and comprehensive onboarding guides directly from a codebase. It scans the repository, detects architectural patterns, identifies technical layers (presentation, business logic, data access), and creates two distinct guides: a Principal-Level Guide for seniors and a Zero-to-Hero Path for newcomers, ensuring every detail is cited with specific file paths.

Master the architecture of reliable distributed systems using advanced workflow orchestration patterns. This guide covers fundamental design decisions, including the distinction between Workflows and Activities, and introduces critical patterns like Saga for distributed transactions, Entity Workflows, and Fan-Out/Fan-In. Learn best practices for handling long-running processes, state persistence, and failure recovery to build robust business logic.

Reasoning-Driven Image Briefs skill transforms agent prompts into logic-based Gemini 3 style instructions for muapi.ai, adding structured creative briefs (subject/action/context/composition/lighting), precise text cues, and physics-grounded constraints before invoking generation scripts.

Astropy is a Python library for astronomical research that handles unit-aware quantities, celestial coordinates, FITS files, cosmological models, precise time systems, and tabular data, letting you transform, convert, and analyze observational or theoretical datasets.

LaminDB is a Python-driven open-source framework for managing biological datasets, ensuring traceable, reproducible, FAIR data through lineage tracking, schema validation, ontology annotation, workflow integration, and lakehouse-style querying.

Comprehensive Python toolkit for building, analyzing, and visualizing complex networks; supports algorithms, I/O, generation, and community detection across social, biological, transportation, and citation data.