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Pinecone:Assistant

  • 4 installs
  • 67 repo stars
  • Updated July 17, 2026
  • pinecone-io/pinecone-claude-code-plugin

Creates, manages, and chats with Pinecone Assistants for document Q&A with citations using bundled create, upload, sync, and chat scripts.

About

Runs Pinecone Assistant operations for managed RAG, from creating an assistant and uploading docs to chatting and retrieving cited context. A developer uses it to build document Q&A without embedding pipelines.

  • Managed RAG: upload docs, ask questions, get cited answers
  • Scripts for create, upload, sync, chat, context, and list

Pinecone:Assistant by the numbers

  • 4 all-time installs (skills.sh)
  • Ranked #13,372 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/pinecone-io/pinecone-claude-code-plugin --skill pineconeassistant

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Installs4
repo stars67
Last updatedJuly 17, 2026
Repositorypinecone-io/pinecone-claude-code-plugin

What it does

Creates, manages, and chats with Pinecone Assistants for document Q&A with citations using bundled create, upload, sync, and chat scripts.

Files

SKILL.mdMarkdownGitHub ↗

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

What to doScriptKey args
Create an assistantscripts/create.py--name --instructions --region
Upload filesscripts/upload.py--assistant --source --patterns
Sync files (incremental)scripts/sync.py--assistant --source --delete-missing --dry-run
Chat / ask a questionscripts/chat.py--assistant --message
Get context snippetsscripts/context.py--assistant --query --top-k
List assistantsscripts/list.py--files --json

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 available — export PINECONE_API_KEY="your-key" (or use a .env file with uv run --env-file .env)
  • uv must be installed — install uv
  • Get a free API key at: https://app.pinecone.io/?sessionType=signup

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