nestjs-best-practices
NestJS 11+ expert assistant for enterprise Node.js development, including dependency injection, DTO validation, authentication, ORMs, testing, microservices, and architectural best practices.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
568 skills found
NestJS 11+ expert assistant for enterprise Node.js development, including dependency injection, DTO validation, authentication, ORMs, testing, microservices, and architectural best practices.
A runtime skill discovery engine for AI agents. Search and retrieve specialized agent skills (SKILL.md) on-demand via REST API or MCP to inject procedural knowledge into your agent's context.
Expert assistant for building modern Next.js 13+ applications using the App Router, including Server Components, nested layouts, streaming with Suspense, and advanced data fetching patterns.
Build, manage, and deploy AI-powered voice assistants, phone bots, and IVR systems with Vapi using the Model Context Protocol (MCP).
Translates Excel (.xlsx) files from English to Chinese while preserving all formatting, images, and charts.
Add evlog framework integration: automate wide-event logging across your stack with standardized middleware, build configurations, testing, and documentation.
Local text-to-speech conversion using Kokoro TTS. Generate audio, read text aloud, and handle multilingual speech synthesis directly in your terminal.
Private skill distribution system for managing agentics across devices and teams. Install, sync, add, and update your agents, skills, and prompts via a central library catalog.
Downloads YouTube videos directly to your ~/Downloads folder using yt-dlp. Supports high-quality audio and video extraction.
GitHub workflow assistant with integrated git and gh CLI support for managing repositories, branches, pull requests, and issues.
Automates the creation and maintenance of CLAUDE.md files. It monitors codebase evolution and keeps project memory in sync with file changes, structure, and build commands.
Normalizes testing defect logs by correcting typos, abbreviations, and ambiguous descriptions based on product-specific codebooks and station validation.