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 assistantgit 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/assistant)<a href="https://agentmods.dev/skills/pinecone-io/gemini-cli-extension/assistant"><img src="https://agentmods.dev/badge/skills/pinecone-io/gemini-cli-extension/assistant/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/assistant"><img src="https://agentmods.dev/badge/skills/pinecone-io/gemini-cli-extension/assistant.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00068 | $0.00806 |
| Opus 5.5 | $0.00027 | $0.00322 |
| Sonnet 5.5 | $0.00014 | $0.00161 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
assistant 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- pinecone-assistant — 97% identical, 7 lines differ
- pinecone-assistant — 89% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pinecone Assistant
Pinecone Assistant is a fully managed RAG service. Upload documents, ask questions, get cited answers. No embedding pipelines or infrastructure required.
All scripts are in
scripts/relative to this skill directory. Run with:uv run scripts/script_name.py [arguments]
Operations
| What to do | Script | Key args |
|---|---|---|
| Create an assistant | scripts/create.py |
--name --instructions --region |
| Upload files | scripts/upload.py |
--assistant --source --patterns |
| Sync files (incremental) | scripts/sync.py |
--assistant --source --delete-missing --dry-run |
| Chat / ask a question | scripts/chat.py |
--assistant --message |
| Get context snippets | scripts/context.py |
--assistant --query --top-k |
| List assistants | scripts/list.py |
--files --json |
For full workflow details on any operation, read the relevant file in references/.
Natural Language Recognition
Proactively handle these patterns without requiring explicit commands:
Create: "create an assistant", "make an assistant called X", "set up an assistant for my docs" → See references/create.md
Upload: "upload my docs", "add files to my assistant", "index my documentation" → See references/upload.md
Sync: "sync my docs", "update my assistant", "keep assistant in sync", "refresh from ./docs" → See references/sync.md
Chat: "ask my assistant about X", "what does my assistant know about X", "chat with X" → See references/chat.md
Context: "search my assistant for X", "find context about X" → See references/context.md
List: "show my assistants", "what assistants do I have"
→ Run uv run scripts/list.py
Conversation Memory
Track the last assistant used within the conversation:
- When a user creates or first uses an assistant, remember its name
- If user says "my assistant", "it", or "the assistant" → use the last one
- Briefly confirm which assistant you're using: "Asking docs-bot..."
- If ambiguous and multiple exist → ask the user to clarify
What ships with it
12 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.
- references/chat.md 1.2 KB
- references/context.md 1.5 KB
- references/create.md 1.5 KB
- references/list.md 713 B
- references/sync.md 1.9 KB
- references/upload.md 1.7 KB
- scripts/chat.py 4.9 KB runs code
- scripts/context.py 5.7 KB runs code
- scripts/create.py 3.9 KB runs code
- scripts/list.py 7.8 KB runs code
- scripts/sync.py 13 KB runs code
- scripts/upload.py 7.5 KB runs code
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 · 79 lines · 68 tokens per session scan A 04f7e688221a
assistant is a skill published in the GitHub repository pinecone-io/gemini-cli-extension (23 stars, last pushed 2mo ago), licensed MIT. It adds 68 tokens to every session and 806 once invoked, about $0.0003 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: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.
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:query
Query integrated indexes using text with Pinecone MCP. IMPORTANT - This skill ONLY works with integrated indexes (indexes with built-in Pinecone embedding models like multilingual-e5-large). For standard indexes or advanced vector operations, use the pinecone:cli skill instead. Requires PINECONEAPIKEY environment…