Total 50,510 skills, AI & Machine Learning has 8479 skills
Showing 12 of 8479 skills
Calculate MFU (Machine FLOP Utilization) for operators such as matmul/GEMM, and provide clear formulas and derivation processes.
MindSpeed-LLM 环境搭建指南，用于华为昇腾 NPU。覆盖 CANN 环境激活、PyTorch + torch_npu 安装、MindSpeed 加速库安装、Megatron-LM 核心模块集成、MindSpeed-LLM 安装及环境验证。当用户需要在昇腾 NPU 上搭建 MindSpeed-LLM 训练环境时使用。
Multi-Harness Portability is the engineering discipline of writing agent skills, prompts, and configurations that work across every major AI coding harness — Claude Code, Cursor, Codex, Gemini CLI, OpenCode, and beyond.
Manage skills across 20+ AI platforms (Claude Code, Cursor, Copilot, Gemini, OpenClaw, Hermes, etc.). Use `list` as the unified entrypoint. Default behavior is listing skills only; only guide/recommend when the user explicitly asks what skill to use.
Manages the ai-context/ memory layer: initialize from scratch, update with session work, or maintain/cleanup. Trigger: /memory-init, /memory-update, /memory-maintain, initialize memory, update memory, maintain memory.
Full production pipeline — story to scenes, Z-Image start frames, Qwen Edit end frames, WAN FLF video clips, ffmpeg concatenation
oh-my-agent project setup verification and configuration
Stability AI integration. Manage data, records, and automate workflows. Use when the user wants to interact with Stability AI data.
Command-line interface for ChromaDB - A stateless CLI for managing vector database collections, documents, and semantic search. Designed for AI agents and automation via the ChromaDB HTTP API v2.
Interactive CLI for Uni-Mol molecular property prediction training and inference workflows.
Build type-safe LLM applications with DSPy.rb — Ruby's programmatic prompt framework with signatures, modules, agents, and optimization. Use when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers, building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
Quick install and deploy vLLM, start serving with a simple LLM, and test OpenAI API.