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 skills add pinecone-io/gemini-cli-extension --skill helpgit clone --depth 1 https://github.com/pinecone-io/gemini-cli-extensionWrote 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/gemini-cli-extension/help)<a href="https://agentmods.dev/skills/pinecone-io/gemini-cli-extension/help"><img src="https://agentmods.dev/badge/skills/pinecone-io/gemini-cli-extension/help/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pinecone-io/gemini-cli-extension/help"><img src="https://agentmods.dev/badge/skills/pinecone-io/gemini-cli-extension/help.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00050 | $0.00687 |
| Opus 5.5 | $0.00020 | $0.00275 |
| Sonnet 5.5 | $0.00010 | $0.00137 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 67 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.
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 either export it in your terminal:
export PINECONE_API_KEY="your-key"
Optional (unlock more capabilities)
| Tool | What it enables | Install |
|---|---|---|
| Pinecone MCP server | Use Pinecone directly inside your AI agent/IDE without writing code | Already installed for you in Gemini CLI! |
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 |
|---|---|
quickstart |
Step-by-step onboarding — create an index, upload data, and run your first search |
query |
Search integrated indexes using natural language text via the Pinecone MCP |
cli |
Use the Pinecone CLI (pc) for terminal-based index and vector management |
assistant |
Create, manage, and chat with Pinecone Assistants for document Q&A with citations |
mcp |
Reference for all Pinecone MCP server tools and their parameters |
pinecone-docs |
Curated links to official Pinecone documentation, organized by topic |
Which skill should I use?
Just getting started? → quickstart
Want to search an index you already have?
- Integrated index (built-in embedding model) →
query(uses MCP) - Any other index type →
cli
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.
- 1mo ago First seen · 67 lines · 50 tokens per session scan A 37a6d178a03e
help is a skill published in the GitHub repository pinecone-io/gemini-cli-extension (23 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 687 once invoked, about $0.0002 per session on Opus 5.5. 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
pinecone:full-text-search
Create, ingest into, and query a Pinecone full-text-search (FTS) document index using the graduated document-schema API (Python SDK 10.0.0, API version 2026-07). Use when the user or agent asks to build a text search index on Pinecone, add dense or sparse vector fields, ingest documents, construct scoreby clauses…
pinecone: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…
pinecone: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:mcp
Reference for the Pinecone MCP server tools. Documents all available tools - list-indexes, describe-index, describe-index-stats, create-index-for-model, upsert-records, search-records, cascading-search, and rerank-documents. Use when an agent needs to understand what Pinecone MCP tools are available, how to use them…
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.
pinecone-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…