productivity▌

JavaScript SDK for building features in existing Base44 projects with CRUD operations, authentication, AI agents, and backend functions. \n \n Provides modules for entities (data models), auth, agents, functions, integrations (AI, email, file uploads), analytics, and user management \n Requires an initialized Base44 project with base44/config.jsonc ; use base44-cli skill for new project setup \n Includes critical API reference tables to prevent hallucination of method names (e.g., loginViaEmailP

Initialize, configure, and deploy Base44 projects via CLI commands for entities, functions, agents, and site hosting. \n \n Handles project creation, authentication, and resource management through npx base44 commands; check base44/config.jsonc existence to determine whether to use this skill (new projects) or hand off to base44-sdk (existing projects) \n Supports entity schema definition, backend function deployment with automations (CRON, entity hooks, scheduled triggers), agent configuration,

Detects and transforms AI-generated Korean text patterns into natural human writing. \n \n Analyzes 24 distinct linguistic patterns across five categories (punctuation, spacing, part-of-speech diversity, vocabulary, structure) grounded in empirical research from the KatFishNet paper (94.88% AUC accuracy for comma patterns) \n Identifies common LLM markers in Korean: excessive commas, rigid spacing consistency, noun overuse, AI buzzwords, and monotonous sentence rhythm \n Rewrites detected text t

Comprehensive digital forensics and signal analysis toolkit for CTF challenges across disk, memory, network, and steganography domains. \n \n Covers 15+ forensics categories: disk/memory imaging (Volatility, VM forensics, coredumps), Windows registry/event logs/SAM, Linux logs/Docker, network analysis (PCAP, TLS decryption, SMB, NTLMv2), and browser artifact extraction \n Includes advanced steganography techniques: image LSB/bitplane extraction, PDF multi-layer stego, audio DTMF/FFT/SSTV, SVG ke

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你是 dontbesilent 的执行力诊断 AI。你的任务是帮用户搞清楚：为什么他知道该做什么，但就是不做。

macOS UI automation CLI for screen capture, element targeting, and input control. \n \n Covers 30+ commands across screen capture, UI inspection, app/window management, interaction (click, drag, type, scroll), and system control (menus, Dock, dialogs, clipboard) \n Targets UI elements by ID, query, or coordinates; supports snapshot caching and --json output for scripting \n Includes vision capabilities ( see command) for annotated UI maps and optional AI analysis of screen content \n Requires Sc

Modern .NET 10 and C# 14 patterns for minimal APIs, modular monoliths, and resilient applications. \n \n Covers C# 14 syntax (extension blocks, field keyword, null-conditional assignment) and .NET 10 minimal APIs with validation, TypedResults, and modular architecture \n Includes security patterns: JWT authentication, CORS, rate limiting, middleware ordering, and RFC 9457 problem details \n Provides infrastructure guidance on Options pattern variants (IOptions, IOptionsSnapshot, IOptionsMonitor)

Build three content-fetching and learning skills by creating fetch-tweet, fetch-youtube, and content-digest from scratch. \n \n Learn a two-phase workflow (EXPLAIN + EXECUTE in turn 1, QUIZ in turn 2) that enforces hands-on practice before assessment \n Create fetch-tweet to retrieve and translate X/Twitter content via API, then fetch-youtube to extract and correct YouTube captions using yt-dlp and web search \n Build content-digest with Quiz-First learning methodology, which improves retention