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-cursor-plugin/pinecone-helpnpx skills add pinecone-io/pinecone-cursor-plugin --skill pinecone-helpgit clone --depth 1 https://github.com/pinecone-io/pinecone-cursor-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 | $0.00052 | $0.00924 |
| Opus 5 | $0.00026 | $0.00462 |
| Sonnet 5 | $0.00010 | $0.00185 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
pinecone-help 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.
This is a copy
86% identical to pinecone-help — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinecone Skills — Help & Overview
Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. It's useful for building semantic search, retrieval augmented generation, recommendation systems, and agentic applications.
Here's everything you need to get started and a summary of all available skills.
Invoke any skill from Cursor Agent chat with /pinecone-<skill-name> — for example /pinecone-quickstart or /pinecone-n8n.
What You Need
Required
- Pinecone account — free to create at https://app.pinecone.io/?sessionType=signup
- API key — create one in the Pinecone console after signing up, then make it
available to this environment:
- Add
PINECONE_API_KEY=your-keyto a.envfile at your workspace root. The bundled MCP config reads it through Cursor'senvFilefield.
- Add
- For scripts, either
export PINECONE_API_KEY="your-key"in your terminal or run them withuv run --env-file .env scripts/....
Optional (unlock more capabilities)
| Tool | What it enables | Install |
|---|---|---|
| Pinecone MCP server | Use Pinecone directly inside your AI agent/IDE without writing code | Setup guide |
Pinecone CLI (pc) |
Manage all index types from the terminal, batch operations, backups, CI/CD | brew tap pinecone-io/tap && brew install pinecone-io/tap/pinecone |
| uv | Run the packaged Python scripts included in these skills | Install uv |
Available Skills
| Skill | What it does |
|---|---|
pinecone-quickstart |
Step-by-step onboarding — create an index, upload data, and run your first search |
pinecone-query |
Search integrated indexes using natural language text via the Pinecone MCP |
pinecone-cli |
Use the Pinecone CLI (pc) for terminal-based index and vector management |
pinecone-assistant |
Create, manage, and chat with Pinecone Assistants for document Q&A with citations |
pinecone-mcp |
Reference for all Pinecone MCP server tools and their parameters |
pinecone-full-text-search |
Build a full-text-search index — schema design, safe bulk ingestion, and query construction (text / query_string / dense / sparse scoring with text-match and metadata filters). Preview API (2026-01.alpha); requires pinecone Python SDK ≥ 9.0. |
pinecone-docs |
Curated links to official Pinecone documentation, organized by topic |
pinecone-n8n |
Build n8n workflows with the Pinecone Assistant node or Pinecone Vector Store node, including best practices and full workflow JSON generation |
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 · 71 lines · 52 tokens per session scan A 2476d8de896b
pinecone-help is a skill published in the GitHub repository pinecone-io/pinecone-cursor-plugin (1 stars, last pushed 18d ago), licensed MIT. It adds 52 tokens to every session and 924 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to pinecone-help, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
ai-ab-testing
Skill "ai-ab-testing" from skillsaiagent/aiskills, covering ai-ab-testing a/b 测试设计助手, 概述, 什么时候使用, 调用方式 and 命令示例.
ai-accessibility
无障碍体验诊断助手适合内容创作者、市场营销、运营、内容媒体在用户提出“这个页面好用吗”这类问题，需要快速拆解目标、判断重点并形成可执行结果时使用，帮助基于输入材料生成问题归因、服务改进建议、SOP 或 FAQ 清单。.
ai-account-research-sales-card
销售增长助手适合销售、市场营销、运营、产品在用户提出“客户为什么不推进”这类问题，需要快速拆解目标、判断重点并形成可执行结果时使用，帮助基于输入材料生成摘要、诊断结论、行动建议和可复用交付物。.
ai-account-research
客户研究助手适合市场营销、运营、software、教育培训在用户提出“这个客户怎么切入”这类问题，需要快速拆解目标、判断重点并形成可执行结果时使用，帮助基于输入材料生成销售策略、沟通素材、跟进计划。.
ai-ad-copy-compliance-review
风险审阅助手适合运营、市场营销、销售、法务在用户提出“这里有什么风险”这类问题，需要快速拆解目标、判断重点并形成可执行结果时使用，帮助基于输入材料生成摘要、诊断结论、行动建议和可复用交付物。.
ai-ad-creative-review
文案诊断助手适合市场营销、运营、产品、销售在用户提出“这段文案能打动人吗”这类问题，需要快速拆解目标、判断重点并形成可执行结果时使用，帮助基于输入材料生成摘要、诊断结论、行动建议和可复用交付物。.