Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/pinecone-io/pinecone-claude-code-plugin/quickstartnpx skills add pinecone-io/pinecone-claude-code-plugin --skill quickstartgit clone --depth 1 https://github.com/pinecone-io/pinecone-claude-code-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00079 | $0.02213 |
| Opus 5 | $0.00039 | $0.01107 |
| Sonnet 5 | $0.00016 | $0.00443 |
| Haiku 4.5 | $0.00008 | $0.00221 |
Grade A, and why
pinecone:quickstart scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- pinecone-quickstart — 91% identical, 37 lines differ
- pinecone-quickstart — 91% identical, 31 lines differ
- quickstart — 88% identical, 36 lines differ
How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinecone Quickstart
Welcome! This skill walks you through your first Pinecone experience using the tools available to you. In this quickstart, you will learn how to do a simple form of semantic search over some example data.
Whenever this skill asks the user to choose between options, confirm a destructive step, or pick from a list, use the AskUserQuestion tool rather than plain prose. Fall back to prose only if the tool is unavailable.
Prerequisites
Before starting either path, verify the API key works by calling list-indexes via the Pinecone MCP. If it succeeds, proceed. If it fails, ask the user to set their key:
- Run
export PINECONE_API_KEY="your-key"in your terminal. Claude Code reads your shell environment, so this is enough. - To use a
.envfile instead, run scripts withuv run --env-file .env scripts/....
Then retry list-indexes to confirm.
Step 0: Choose Your Path
Ask the user which path they want:
- Database – Build a vector search index. Best for developers who want to store and search embeddings. Uses the Pinecone MCP + a Python upsert script.
- Assistant – Build a document Q&A assistant. Best for users who want to upload files and ask questions with cited answers. No code required.
Path A: Database Quickstart
For each step, explain to the user what will happen. An overview is here:
- Check if MCP is set
- Create an integrated index with MCP
- Upsert sample data using the bundled script (9 sentences across productivity, health, and nature themes)
- Run a semantic search query and explore further queries
- Optionally try reranking
- Offer the complete standalone script
Step 1 – Verify MCP is Available
The prerequisite check already called list-indexes. If it succeeded, the MCP is working — proceed to Step 2.
If it failed because MCP tools were unavailable (not an auth error):
- Tell the user the MCP server needs to be configured
- Point them to: https://docs.pinecone.io/reference/tools/mcp
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 231 lines · 79 tokens per session scan A e2335071734d
pinecone:quickstart is a skill published in the GitHub repository pinecone-io/pinecone-claude-code-plugin (68 stars, last pushed 18d ago), licensed MIT. It adds 79 tokens to every session and 2,213 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
help
Overview of all available Pinecone skills and what a user needs to get started. Invoke when a user asks what skills are available, how to get started with Pinecone, or what they need to set up before using any Pinecone skill.
assistant
Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create, upload, sync, chat, context retrieval, and list. Recognizes natural language like "create an assistant from my docs", "ask my assistant about X", or "upload my docs to Pinecone".
pinecone-help
Overview of all available Pinecone skills and what a user needs to get started. Invoke when a user asks what skills are available, how to get started with Pinecone, or what they need to set up before using any Pinecone skill.
quickstart
Interactive Pinecone quickstart for new developers. Choose between two paths - Database (create an integrated index, upsert data, and query using Pinecone MCP + Python) or Assistant (create a Pinecone Assistant for document Q&A). Use when a user wants to get started with Pinecone for the first time or wants a guided…
cli
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation…
pinecone-n8n
Build n8n workflows using the Pinecone Assistant node or Pinecone Vector Store node. Use when building RAG pipelines, chat-with-docs workflows, configuring Pinecone nodes in n8n, troubleshooting Pinecone n8n nodes, or asking about best practices for Pinecone in n8n.