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Generate personalized, compelling cover letters from resume and job description inputs. \n \n Creates 250-400 word cover letters with research-backed opening hooks, direct experience-to-requirement matching, and confident closing calls to action \n Provides five opening strategies (company knowledge, mutual connections, problem-solving, achievements, industry insights) plus body paragraph frameworks for addressing qualification gaps \n Includes industry-specific guidance for tech, marketing, fin

Skill by ara.so — Daily 2026 Skills collection

Comprehensive trading plan framework with risk management, position sizing, entry/exit rules, and performance tracking. \n \n Covers five trading styles (day, swing, position, options, investing) with specific rules and best practices for each \n Includes mandatory risk management components: 1% rule, 2R minimum reward-to-risk, position sizing formulas, and daily loss limits to prevent account blowup \n Provides detailed entry and exit strategies using technical patterns, support/resistance, ATR

Guides homepage content, structure, and conversion optimization.

Generate Xiaohongshu-style cover images from user topics with automatic formatting. \n \n Accepts a topic as input and produces vertically-oriented 3:4 cover images optimized for mobile viewing \n Requires API key from https://api.canghe.ai/ (via CANGHE_API_KEY environment variable or direct argument) \n Saves generated images to the current working directory with timestamped filenames ( xiaohongshu-cover-{timestamp}.png ) \n Applies clean, youthful aesthetic with automatic watermark removal and

Automatically generate comprehensive API documentation from your codebase with endpoints, examples, and best practices. \n \n Analyzes REST, GraphQL, and WebSocket APIs to extract endpoints, parameters, authentication, and error patterns \n Generates endpoint documentation with request/response specifications, code examples in multiple languages (cURL, JavaScript, Python), and error handling details \n Produces OpenAPI/Swagger specifications and Postman collections for interactive testing and AP

Technology-agnostic prompt generator for identifying and documenting high-quality code exemplars across multiple languages. \n \n Supports seven programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with auto-detection capability \n Configurable analysis depth (Basic, Standard, Comprehensive), categorization method (Pattern Type, Architecture Layer, File Type), and documentation format \n Generates exemplars.md files with real file references, descriptions, and optio

Generates detailed implementation blueprints by analyzing project architecture, technology stacks, and workflow patterns. \n \n Auto-detects project type, entry points, persistence mechanisms, and architecture patterns (.NET, Java/Spring, React, microservices, etc.) to tailor documentation \n Documents complete end-to-end workflows across entry points, service layers, data access, error handling, and response construction with actual code examples \n Configurable output detail levels, workflow c

Generate production-ready MCP servers in Ruby using the official SDK with complete project scaffolding. \n \n Generates a full project structure with tools, prompts, resources, tests, and configuration files following Ruby conventions \n Includes input/output schemas, tool annotations, and structured content support for type-safe MCP implementations \n Provides example tools (greet, calculate), prompts (code review), and resources with comprehensive test coverage using Minitest \n Supports stdio

Analyzes project folder structures across multiple technology stacks and generates comprehensive organization blueprints. \n \n Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter) and identifies architectural patterns including monorepos, microservices, and frontend components \n Generates detailed blueprints with customizable visualization styles (ASCII tree, markdown lists, or tables) and configurable depth levels \n Documents file placement patterns, naming conve