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Recognizes natural language like \"create an assistant from my docs\", \"ask my assistant about X\", or \"upload my docs to Pinecone\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"pinecone","Pinecone","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fpinecone.png","pinecone-io",[13,17,20,23],{"name":14,"slug":15,"type":16},"LLM","llm","tag",{"name":18,"slug":19,"type":16},"Documents","documents",{"name":21,"slug":22,"type":16},"Search","search",{"name":9,"slug":8,"type":16},14,"https:\u002F\u002Fgithub.com\u002Fpinecone-io\u002Fskills","2026-07-13T06:02:40.044479",null,2,[30,31,8,32,33,34],"agent-skills","agents","retrieval-augmented-generation","semantic-search","skills-sh",{"repoUrl":25,"stars":24,"forks":28,"topics":36,"description":37},[30,31,8,32,33,34],"Pinecone's official Agent Skills library, for use with agentic IDEs such as Cursor, Github Copilot, Antigravity, Gemini CLI and more.","https:\u002F\u002Fgithub.com\u002Fpinecone-io\u002Fskills\u002Ftree\u002FHEAD\u002Fskills\u002Fpinecone-assistant","---\nname: pinecone-assistant\ndescription: Create, manage, and chat with Pinecone Assistants for document Q&A with citations. Handles all assistant operations - create, upload, sync, chat, context retrieval, and list. Recognizes natural language like \"create an assistant from my docs\", \"ask my assistant about X\", or \"upload my docs to Pinecone\".\n---\n\n# Pinecone Assistant\n\nPinecone Assistant is a fully managed RAG service. Upload documents, ask questions, get cited answers. No embedding pipelines or infrastructure required.\n\n> All scripts are in `scripts\u002F` relative to this skill directory.\n> Run with: `uv run scripts\u002Fscript_name.py [arguments]`\n\n## Operations\n\n| What to do | Script | Key args |\n|---|---|---|\n| Create an assistant | `scripts\u002Fcreate.py` | `--name` `--instructions` `--region` |\n| Upload files | `scripts\u002Fupload.py` | `--assistant` `--source` `--patterns` |\n| Sync files (incremental) | `scripts\u002Fsync.py` | `--assistant` `--source` `--delete-missing` `--dry-run` |\n| Chat \u002F ask a question | `scripts\u002Fchat.py` | `--assistant` `--message` |\n| Get context snippets | `scripts\u002Fcontext.py` | `--assistant` `--query` `--top-k` |\n| List assistants | `scripts\u002Flist.py` | `--files` `--json` |\n\nFor full workflow details on any operation, read the relevant file in `references\u002F`.\n\n---\n\n## Natural Language Recognition\n\nProactively handle these patterns without requiring explicit commands:\n\n**Create:** \"create an assistant\", \"make an assistant called X\", \"set up an assistant for my docs\"\n→ See [references\u002Fcreate.md](references\u002Fcreate.md)\n\n**Upload:** \"upload my docs\", \"add files to my assistant\", \"index my documentation\"\n→ See [references\u002Fupload.md](references\u002Fupload.md)\n\n**Sync:** \"sync my docs\", \"update my assistant\", \"keep assistant in sync\", \"refresh from .\u002Fdocs\"\n→ See [references\u002Fsync.md](references\u002Fsync.md)\n\n**Chat:** \"ask my assistant about X\", \"what does my assistant know about X\", \"chat with X\"\n→ See [references\u002Fchat.md](references\u002Fchat.md)\n\n**Context:** \"search my assistant for X\", \"find context about X\"\n→ See [references\u002Fcontext.md](references\u002Fcontext.md)\n\n**List:** \"show my assistants\", \"what assistants do I have\"\n→ Run `uv run scripts\u002Flist.py`\n\n---\n\n## Conversation Memory\n\nTrack the last assistant used within the conversation:\n- When a user creates or first uses an assistant, remember its name\n- If user says \"my assistant\", \"it\", or \"the assistant\" → use the last one\n- Briefly confirm which assistant you're using: \"Asking docs-bot...\"\n- If ambiguous and multiple exist → ask the user to clarify\n\n---\n\n## Multi-Step Requests\n\nHandle chained requests naturally. Example:\n\n> \"Create an assistant called docs-bot, upload my .\u002Fdocs folder, and ask what the main features are\"\n\n1. `uv run scripts\u002Fcreate.py --name docs-bot`\n2. `uv run scripts\u002Fupload.py --assistant docs-bot --source .\u002Fdocs`\n3. `uv run scripts\u002Fchat.py --assistant docs-bot --message \"what are the main features?\"`\n\n---\n\n## Prerequisites\n\n- `PINECONE_API_KEY` must be available — terminal: `export PINECONE_API_KEY=\"your-key\"`, or add to a `.env` file and run scripts with `uv run --env-file .env scripts\u002F...`\n- `uv` must be installed — [install uv](https:\u002F\u002Fdocs.astral.sh\u002Fuv\u002Fgetting-started\u002Finstallation\u002F)\n- Get a free API key at: https:\u002F\u002Fapp.pinecone.io\u002F?sessionType=signup\n",{"data":41,"body":42},{"name":4,"description":6},{"type":43,"children":44},"root",[45,53,59,83,90,353,366,370,376,381,398,413,428,443,458,474,477,483,488,513,516,522,527,535,566,569,575],{"type":46,"tag":47,"props":48,"children":49},"element","h1",{"id":4},[50],{"type":51,"value":52},"text","Pinecone Assistant",{"type":46,"tag":54,"props":55,"children":56},"p",{},[57],{"type":51,"value":58},"Pinecone Assistant is a fully managed RAG service. 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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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[694,695,698],{"name":671,"slug":672,"type":16},{"name":696,"slug":697,"type":16},"Onboarding","onboarding",{"name":9,"slug":8,"type":16},"2026-07-13T06:02:37.342095",{"slug":701,"name":701,"fn":702,"description":703,"org":704,"tags":705,"stars":24,"repoUrl":25,"updatedAt":711},"pinecone-mcp","reference Pinecone MCP server tools","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, or what parameters they accept.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[706,707,710],{"name":671,"slug":672,"type":16},{"name":708,"slug":709,"type":16},"MCP","mcp",{"name":9,"slug":8,"type":16},"2026-07-13T06:02:33.158312",{"slug":713,"name":713,"fn":714,"description":715,"org":716,"tags":717,"stars":24,"repoUrl":25,"updatedAt":727},"pinecone-n8n","build RAG workflows with Pinecone and 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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[718,720,721,724],{"name":719,"slug":719,"type":16},"n8n",{"name":9,"slug":8,"type":16},{"name":722,"slug":723,"type":16},"RAG","rag",{"name":725,"slug":726,"type":16},"Workflow Automation","workflow-automation","2026-07-13T06:02:34.599969",9,{"items":730,"total":847},[731,745,754,764,773,783,794,804,816,828,835,841],{"slug":732,"name":733,"fn":5,"description":6,"org":734,"tags":735,"stars":742,"repoUrl":743,"updatedAt":744},"pineconeassistant","pinecone:assistant",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[736,739,740,741],{"name":737,"slug":738,"type":16},"Knowledge Management","knowledge-management",{"name":14,"slug":15,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},67,"https:\u002F\u002Fgithub.com\u002Fpinecone-io\u002Fpinecone-claude-code-plugin","2026-07-13T06:02:15.573985",{"slug":746,"name":747,"fn":652,"description":653,"org":748,"tags":749,"stars":742,"repoUrl":743,"updatedAt":753},"pineconecli","pinecone:cli",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[750,751,752],{"name":657,"slug":658,"type":16},{"name":660,"slug":661,"type":16},{"name":9,"slug":8,"type":16},"2026-07-13T06:02:07.032383",{"slug":755,"name":756,"fn":666,"description":667,"org":757,"tags":758,"stars":742,"repoUrl":743,"updatedAt":763},"pineconedocs","pinecone:docs",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[759,760,761,762],{"name":671,"slug":672,"type":16},{"name":9,"slug":8,"type":16},{"name":675,"slug":676,"type":16},{"name":21,"slug":22,"type":16},"2026-07-13T06:02:12.996533",{"slug":765,"name":766,"fn":680,"description":681,"org":767,"tags":768,"stars":742,"repoUrl":743,"updatedAt":772},"pineconefull-text-search","pinecone:full-text-search",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[769,770,771],{"name":660,"slug":661,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},"2026-07-13T06:02:18.270055",{"slug":774,"name":775,"fn":776,"description":691,"org":777,"tags":778,"stars":742,"repoUrl":743,"updatedAt":782},"pineconehelp","pinecone:help","provide Pinecone skill guidance",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[779,780,781],{"name":671,"slug":672,"type":16},{"name":9,"slug":8,"type":16},{"name":675,"slug":676,"type":16},"2026-07-13T06:02:11.702305",{"slug":784,"name":785,"fn":786,"description":703,"org":787,"tags":788,"stars":742,"repoUrl":743,"updatedAt":793},"pineconemcp","pinecone:mcp","use Pinecone MCP server tools",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[789,790,791,792],{"name":660,"slug":661,"type":16},{"name":708,"slug":709,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},"2026-07-16T05:59:21.318686",{"slug":795,"name":796,"fn":714,"description":715,"org":797,"tags":798,"stars":742,"repoUrl":743,"updatedAt":803},"pineconen8n","pinecone:n8n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[799,800,801,802],{"name":719,"slug":719,"type":16},{"name":9,"slug":8,"type":16},{"name":722,"slug":723,"type":16},{"name":725,"slug":726,"type":16},"2026-07-13T06:02:05.735702",{"slug":805,"name":806,"fn":807,"description":808,"org":809,"tags":810,"stars":742,"repoUrl":743,"updatedAt":815},"pineconequery","pinecone:query","query Pinecone integrated indexes with text","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 CLI skill instead. Requires PINECONE_API_KEY environment variable and Pinecone MCP server to be configured.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[811,812,813,814],{"name":660,"slug":661,"type":16},{"name":708,"slug":709,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},"2026-07-13T06:02:14.255922",{"slug":817,"name":818,"fn":819,"description":820,"org":821,"tags":822,"stars":742,"repoUrl":743,"updatedAt":827},"pineconequickstart","pinecone:quickstart","run interactive Pinecone quickstart for developers","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 tour of Pinecone's tools.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[823,824,825,826],{"name":660,"slug":661,"type":16},{"name":708,"slug":709,"type":16},{"name":696,"slug":697,"type":16},{"name":9,"slug":8,"type":16},"2026-07-13T06:02:16.886569",{"slug":4,"name":4,"fn":5,"description":6,"org":829,"tags":830,"stars":24,"repoUrl":25,"updatedAt":26},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[831,832,833,834],{"name":18,"slug":19,"type":16},{"name":14,"slug":15,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},{"slug":651,"name":651,"fn":652,"description":653,"org":836,"tags":837,"stars":24,"repoUrl":25,"updatedAt":663},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[838,839,840],{"name":657,"slug":658,"type":16},{"name":660,"slug":661,"type":16},{"name":9,"slug":8,"type":16},{"slug":665,"name":665,"fn":666,"description":667,"org":842,"tags":843,"stars":24,"repoUrl":25,"updatedAt":677},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[844,845,846],{"name":671,"slug":672,"type":16},{"name":9,"slug":8,"type":16},{"name":675,"slug":676,"type":16},18]