Total 34,490 skills
Showing 12 of 34490 skills
Use when building NestJS applications requiring modular architecture, dependency injection, or TypeScript backend development. Invoke for modules, controllers, services, DTOs, guards, interceptors, TypeORM/Prisma.
Build production-ready Express.js servers with middleware, authentication, routing, and database integration. Use when creating REST APIs, managing requests/responses, implementing middleware chains, and handling server logic.
Comprehensive Polymarket skill covering prediction markets, API, trading, market data, and real-time WebSocket data streaming. Build applications with Polymarket services, monitor live trades, and integrate market predictions.
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.
Use when building MCP servers or clients that connect AI systems with external tools and data sources. Invoke for MCP protocol compliance, TypeScript/Python SDKs, resource providers, tool functions.
Generate app icons for your React Native Expo app with iOS 26 support
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
How to debug tursodb using Bytecode comparison, logging, ThreadSanitizer, deterministic simulation, and corruption analysis tools
General guidelines for Commits, formatting, CI, dependencies, security
Use when designing prompts for LLMs, optimizing model performance, building evaluation frameworks, or implementing advanced prompting techniques like chain-of-thought, few-shot learning, or structured outputs.
PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.