Pinecone Assistant

Pinecone Assistant is a fully managed RAG service. Upload documents, ask questions, get cited answers. No embedding pipelines or infrastructure required.

All scripts are in scripts/ relative to this skill directory. Run with: uv run scripts/script_name.py [arguments]

Operations

For full workflow details on any operation, read the relevant file in references/.

Natural Language Recognition

Proactively handle these patterns without requiring explicit commands:

Create: “create an assistant”, “make an assistant called X”, “set up an assistant for my docs” → See references/create.md

Upload: “upload my docs”, “add files to my assistant”, “index my documentation” → See references/upload.md

Sync: “sync my docs”, “update my assistant”, “keep assistant in sync”, “refresh from ./docs” → See references/sync.md

Chat: “ask my assistant about X”, “what does my assistant know about X”, “chat with X” → See references/chat.md

Context: “search my assistant for X”, “find context about X” → See references/context.md

List: “show my assistants”, “what assistants do I have” → Run uv run scripts/list.py

Conversation Memory

Track the last assistant used within the conversation:

• When a user creates or first uses an assistant, remember its name
• If user says “my assistant”, “it”, or “the assistant” → use the last one
• Briefly confirm which assistant you’re using: “Asking docs-bot…”
• If ambiguous and multiple exist → use AskUserQuestion to clarify

Multi-Step Requests

Handle chained requests naturally. Example:

“Create an assistant called docs-bot, upload my ./docs folder, and ask what the main features are”

1. uv run scripts/create.py --name docs-bot
2. uv run scripts/upload.py --assistant docs-bot --source ./docs
3. uv run scripts/chat.py --assistant docs-bot --message "what are the main features?"

Prerequisites

• PINECONE_API_KEY must be set in the environment
• uv must be installed — install uv
• Get a free API key at: https://app.pinecone.io/?sessionType=signup