By frankxai
Deep technical implementations for Oracle AI architecture: Vector Search, Select AI, NVIDIA NIM, and multi-agent patterns
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npx claudepluginhub frankxai/claude-code-oracle-skills --plugin oracle-ai-architectThe complete library of Agent Skills — AI agents & orchestration, MCP & SDKs, Oracle & cloud, frontend & animation, engineering workflow, content & brand, and creative production. Skills auto-activate when relevant.
The sovereign intelligence substrate — persistent memory, identity, and attested governance for your whole AI fleet across Claude Code, Cursor, Cline, Codex, Gemini CLI & Antigravity. Local-first. Forkable. Built on the Starlight Intelligence Protocol v1.1.1.
ACOS — The Operating System for AI-Powered Creators. Layer-modeled skills, commands, agents, and hooks for content / video / music / visual / brand workflows. Composes a creator-meta substrate with creator-specific implementations.
Design framework-agnostic AI agents using Oracle's Open Agent Specification for portable, interoperable agentic systems
Generate professional OCI architecture diagrams with Python diagrams library (official OCI icons) or Mermaid.js
Oracle Cloud Infrastructure domain. Placeholder for future OCI skills.
Pinecone vector database integration. Streamline your Pinecone development with powerful tools for managing vector indexes, querying data, and rapid prototyping. Use slash commands like /quickstart to generate AGENTS.md files and initialize Python projects and /query to quickly explore indexes. Access the Pinecone MCP server for creating, describing, upserting and querying indexes with Claude. Perfect for developers building semantic search, RAG applications, recommendation systems, and other vector-based applications with Pinecone.
Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage
Claude Code skill pack for Oracle Cloud (24 skills)
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.