Build Retrieval-Augmented Generation (RAG) pipelines by indexing documents from directories, URLs, databases, or APIs into vector stores like Pinecone, Weaviate, Chroma, or pgvector using semantic chunking and embeddings, then creating retrievers with hybrid search, re-ranking, caching, citations, fallback handling, and evaluation metrics.
Battle-tested Claude Code workflows from power users. Self-correcting memory, parallel worktrees, wrap-up rituals, 8 hook types, 5 agents, and the 80/20 AI coding ratio. Install: /plugin marketplace add rohitg00/pro-workflow
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, OpenCode, Cursor, and beyond.
Complete AI coding workflow system. Self-correcting memory + persistent FTS5-indexed research wikis + auto-research loop + multi-LLM council on a single SQLite store. 33 skills, 8 agents, 22 commands, 37 hook scripts across 24 events. Cross-agent via SkillKit.
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.
