productivity▌

Embed native views and web content into Flutter apps across Android, iOS, macOS, and web platforms. \n \n Supports Android Hybrid Composition (native fidelity) and Texture Layer (Flutter performance), iOS/macOS Hybrid Composition, and web full-page or embedded multi-view modes \n Provides complete Dart and native code templates (Kotlin for Android, Swift for iOS/macOS, JavaScript for web) with factory registration patterns \n Requires decision tree upfront to determine target platform and embedd

Background JSON parsing and state management for jank-free Flutter UI rendering. \n \n Provides decision tree for choosing between manual serialization ( dart:convert ) and code generation ( json_serializable ) based on model complexity \n Supports three concurrency strategies: main-thread async/await for small payloads, short-lived Isolate.run() for heavy one-off computations, and long-lived isolates with ReceivePort / SendPort for continuous two-way communication \n Includes platform-aware fal

Fetch Pendle SDK metadata and validate routing configuration via CLI commands. \n \n Query supported chains, aggregators, markets, assets, and market token details from Pendle's hosted API \n Six command categories: info , chains , supported-aggregators , markets , assets , and market-tokens with filtering by chain, activity status, and asset type \n Supports JSON and table output formats; configurable API base URL via flag or environment variable \n Preflight validation available through grimoi

Language and framework-specific security reviews with actionable vulnerability detection and fix guidance. \n \n Supports Python, JavaScript/TypeScript, and Go with framework-specific best practices loaded from a references directory \n Operates in three modes: secure-by-default code generation, passive vulnerability detection during development, and full security audit reports with severity prioritization \n Generates detailed markdown reports with line-number references, impact statements, and

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Answers: "What are crypto funds and VCs holding right now?"

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

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

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

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,