model▌

$22

Skill by ara.so — Daily 2026 Skills collection.

AI text generation and streaming for browser applications via CloudBase SDK. \n \n Supports two providers: Hunyuan (recommended: hunyuan-2.0-instruct-20251111 ) and DeepSeek (recommended: deepseek-v3.2 ) \n Two core methods: generateText() for non-streaming responses and streamText() for incremental text chunks with async iteration \n Requires @cloudbase/js-sdk initialization with anonymous authentication and publishable API key from CloudBase console \n Not suitable for Node.js backends, WeChat

Advanced data modeling tool for complex multi-table schemas with automated relationship management and ER diagram generation. \n \n Designed for enterprise-level scenarios requiring multi-entity relationships, foreign key automation, and visual documentation; most simple table creation should use relational-database-tool directly with SQL \n Generates Mermaid class diagrams following strict type mapping, naming conventions, and constraint rules for consistent schema design \n Supports required/u

AI text and image generation for Node.js backends and CloudBase cloud functions. \n \n Supports text generation (non-streaming and streaming) via Hunyuan and DeepSeek models, with recommended models hunyuan-2.0-instruct-20251111 and deepseek-v3.2 \n Image generation exclusive to Node.js SDK using Hunyuan Image model with configurable size, style, negative prompts, and seed control \n Requires @cloudbase/node-sdk version 3.16.0 or higher; set cloud function timeouts to 60–120 seconds for text ope

Mental models and analogies for understanding Rust ownership, borrowing, and core concepts. \n \n Provides visual analogies (keys, lending, remotes) and mental models for ownership, moves, references, lifetimes, and smart pointers to build correct intuition \n Includes misconception-to-correction mappings for common borrow checker errors (E0382, E0502, E0499, E0106, E0507) with explanations of what safety guarantee each enforces \n Covers language-specific shifts for developers coming from Java,

Repository-grounded threat modeling that maps trust boundaries, assets, and abuse paths to concrete code evidence. \n \n Enumerates entry points, data flows, and trust boundaries anchored to actual repository structure and configuration \n Derives realistic attacker goals tied to specific assets (credentials, PII, integrity-critical state, compute resources) rather than generic checklists \n Prioritizes threats using likelihood and impact reasoning, with explicit assumptions about deployment, au

Model deployment is the process of taking a trained machine learning model and making it available for production use through APIs, web services, or batch processing systems.

Comprehensive Power BI data model design review framework for evaluating architecture, relationships, and optimization. \n \n Covers schema architecture, relationship design, and storage mode strategy with detailed assessment checklists across fact tables, dimensions, cardinality, and filter directions \n Includes three-phase review process: model architecture analysis, performance and scalability evaluation, and maintainability/governance assessment \n Provides specialized review types for pre-