A text-search tool for Pinecone indexes that already include Pinecone’s built-in system for turning text into searchable representations.

Use it to find matching records in Pinecone integrated indexes through natural-language queries.

It lets you search those indexes with ordinary language, but it does not cover standard indexes or advanced operations such as fetching, updating, deleting, or bulk-managing records.

query — Skill by pinecone-io

Install

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.

agentmods

npx agentmods add skills/pinecone-io/gemini-cli-extension/query

Any agent

npx skills add pinecone-io/gemini-cli-extension --skill query

Clone the repo

git clone --depth 1 https://github.com/pinecone-io/gemini-cli-extension

Made for: Claude Code, Codex.

Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,027 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 86% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00068	$0.01027
Opus 5	$0.00034	$0.00513
Sonnet 5	$0.00014	$0.00205
Haiku 4.5	$0.00007	$0.00103

Measured 2d ago against content hash 988b7b24c820, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

query 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.

Origin

This is a copy

86% identical to pinecone:query — 21 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.

skills/query/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pinecone Query Skill

Search for records in Pinecone integrated indexes using natural language text queries via the Pinecone MCP server.

What is this skill for?

This skill provides a simple way to query integrated indexes (indexes with built-in Pinecone embedding models) using text queries. The MCP server automatically converts your text into embeddings and searches the index.

Prerequisites

Required:

✅ Pinecone MCP server must be configured - Check if MCP tools are available
✅ PINECONE_API_KEY environment variable must be set - Get a free API key at https://app.pinecone.io/?sessionType=signup
✅ Index must be an integrated index - Uses Pinecone embedding models (e.g., multilingual-e5-large, llama-text-embed-v2, pinecone-sparse-english-v0)

When NOT to use this skill

Use the CLI skill instead if:

❌ Your index is a standard index (no integrated embedding model)
❌ You need to query with custom vector values (not text)
❌ You need advanced vector operations (fetch by ID, list vectors, bulk operations)
❌ Your index uses third-party embedding models (OpenAI, HuggingFace, Cohere)

MCP Limitation: The Pinecone MCP currently only supports integrated indexes. For all other use cases, use the Pinecone CLI skill.

How it works

Utilize Pinecone MCP's search-records tool to search for records within a specified Pinecone integrated index using a text query.

Workflow

IMPORTANT: Before proceeding, verify the Pinecone MCP tools are available. If MCP tools are not accessible:

Inform the user that the Pinecone MCP server needs to be configured
Check if PINECONE_API_KEY environment variable is set
Direct them to the MCP setup documentation or the help skill

Parse the user's input for:
- query (required): The text to search for.
- index (required): The name of the Pinecone index to search.
- namespace (optional): The namespace within the index.
- reranker (optional): The reranking model to use for improved relevance.

Read the full file on GitHub · 84 lines

Changes

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 · 84 lines · 68 tokens per session scan A 988b7b24c820

Subscribe to this mod's changes

query is a skill published in the GitHub repository pinecone-io/gemini-cli-extension (23 stars, last pushed 19d ago), licensed MIT. It adds 68 tokens to every session and 1,027 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:query, differing in 21 lines, and is treated as a copy.

Data and AI Databases RAG and vectors agent-skills gemini-cli gemini-cli-extension pinecone retrieval-augmented-generation semantic-search

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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…

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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…

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