pinecone

Install

Runs in a terminal with Node.js 18 or newer. Add -y to skip the prompts and -g to install for every project instead of this one.

What it does

Pinecone - Managed Vector Database The vector database for production AI applications. When to use Pinecone Use when: - Need managed, serverless vector database - Production RAG applications - Auto-scaling required - Low latency critical (<100ms) - Don't want to manage infrastructure - Need hybrid search (dense + sparse vectors) Metrics: - Fully managed SaaS - Auto-scales to billions of vectors - p95 latency <100ms - 99.9% uptime SLA Use alternatives instead: - Chroma: Self-hosted, open-source - FAISS: Offline, pure similarity search - Weaviate: Self-hosted with more features Quick start…

Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.

Categories

• AI & agents
• Database

Related skills

• faiss

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

  1.0K installs 14KResearchGit & GitHubDatabase
• mlflow

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform

  1.0K installs 14KDeploy & DevOpsGit & GitHub
• serving-llms-vllm

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

  1.0K installs 14KTestingAI & agentsProductivity
• tensorrt-llm

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

  994 installs 14KAI & agentsPython
• peft-fine-tuning

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

  958 installs 14K
• autoresearch

  Orchestra-Research/AI-Research-SKILLs

  Copy install command

  Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

  950 installs 14KResearchAI & agentsOffice documents