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/gemini-cli-extension/quickstartnpx skills add pinecone-io/gemini-cli-extension --skill quickstartgit clone --depth 1 https://github.com/pinecone-io/gemini-cli-extensionWhat 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 | $0.00076 | $0.02125 |
| Opus 5 | $0.00038 | $0.01063 |
| Sonnet 5 | $0.00015 | $0.00425 |
| Haiku 4.5 | $0.00008 | $0.00213 |
Grade A, and why
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.
This is a copy
88% identical to pinecone:quickstart — 36 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 — 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.
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:
- Terminal:
export PINECONE_API_KEY="your-key" - Or create a
.envfile in the project root:PINECONE_API_KEY=your-key
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
Step 2 – Create an Integrated Index
Use the MCP create-index-for-model tool to create a serverless index with integrated embeddings:
name: quickstart-skills
cloud: aws
region: us-east-1
embed:
model: llama-text-embed-v2
fieldMap:
text: chunk_text
Explain to the user what's happening:
- An integrated index uses a built-in Pinecone embedding model (
llama-text-embed-v2) - This means you send plain text and Pinecone handles the embedding automatically
- The
field_maptells Pinecone which field in your records contains the text to embed
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 · 76 tokens per session scan A d3e1da07d767
quickstart is a skill published in the GitHub repository pinecone-io/gemini-cli-extension (23 stars, last pushed 18d ago), licensed MIT. It adds 76 tokens to every session and 2,125 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to pinecone:quickstart, differing in 36 lines, and is treated as a copy.
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