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/n8nnpx skills add pinecone-io/pinecone-claude-code-plugin --skill n8ngit clone --depth 1 https://github.com/pinecone-io/pinecone-claude-code-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pinecone-io/pinecone-claude-code-plugin/n8n)<a href="https://agentmods.dev/skills/pinecone-io/pinecone-claude-code-plugin/n8n"><img src="https://agentmods.dev/badge/skills/pinecone-io/pinecone-claude-code-plugin/n8n.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00067 | $0.07968 |
| Opus 5 | $0.00034 | $0.03984 |
| Sonnet 5 | $0.00013 | $0.01594 |
| Haiku 4.5 | $0.00007 | $0.00797 |
Grade A, and why
pinecone:n8n 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 3d 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
2 near-identical copies found in the catalogue:
- pinecone-n8n — 97% identical, 5 lines differ
- pinecone-n8n — 94% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 693 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinecone n8n Workflow Skill
Invoke this skill from chat with /pinecone:n8n.
This skill helps you build n8n workflows with Pinecone nodes following best practices. It covers two Pinecone nodes:
- Pinecone Assistant (
@pinecone-database/n8n-nodes-pinecone-assistant) — recommended for most use cases - Pinecone Vector Store (
@n8n/n8n-nodes-langchain.vectorStorePinecone) — for advanced control
Core rule: Always use the node's built-in resources and operations. Never suggest using the HTTP node to call the Pinecone REST API directly.
Step 1: Understand the user's scenario
Ask the user what they're trying to do:
- Build a new workflow from scratch
- Configure or understand a specific Pinecone node
- Debug a workflow that isn't working
- Review an existing workflow for best practices
Step 2: Node selection (for new workflows and configuration questions)
Always present the Pinecone Assistant node as the recommended choice first. Do NOT skip this step based on your own inference about which node fits better — even if the use case mentions specific triggers (Google Drive, webhooks, etc.) or file types (text, markdown, PDF), those details do not determine which node to use.
Only skip this step if:
- The user explicitly names a specific node (e.g. "I want to use the Vector Store node", "help me set up pineconeAssistant")
- The user is debugging or configuring an existing workflow that already has a specific Pinecone node in it
If the user has not named a node, always ask or recommend the Assistant node first. If the user said "use defaults" or you cannot ask, default to the Pinecone Assistant node and proceed with the Assistant path.
Ask the user which node they want to use, presenting these two options:
Pinecone Assistant (Recommended)
- Fully managed RAG — Pinecone handles chunking, embedding, and indexing automatically
- Built-in citations with file names and URLs
- Simpler setup: no embedding model or text splitter needed in n8n
- Great for: document Q&A, chat with files, knowledge base search
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.
- 3d ago First seen · 693 lines · 67 tokens per session scan A a17be5a9fdb0
pinecone:n8n is a skill published in the GitHub repository pinecone-io/pinecone-claude-code-plugin (68 stars, last pushed 19d ago), licensed MIT. It adds 67 tokens to every session and 7,968 once invoked, about $0.0003 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.
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help
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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.