pinion-chat

Send a messages array to POST /skill/chat for AI responses with web search.

95|6|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/chu2bard/pinion-os --skill pinion-chat-chu2bard
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pinion-chat
Source: https://github.com/chu2bard/pinion-os/tree/main/skills/chat
Command: npx skills add https://github.com/chu2bard/pinion-os --skill pinion-chat-chu2bard

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Chatting with an AI agent that can augment responses with current web search results, reducing back-and-forth and speeding up information discovery.

Core Features & Use Cases

  • Real-time AI chat with integrated web search for up-to-date information.
  • Context-aware conversations that recall prior messages to maintain flow.
  • Use Case: Quick research chats during product planning, support answering user questions with live data.

Quick Start

Call the POST /skill/chat endpoint with a messages array to receive an AI response.

Frequently Asked Questions about pinion-chat

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use AI chat with integrated web search for real-time research?

AI chat with integrated web search lets you send a messages array to a POST endpoint and receive responses augmented with current web data. This reduces back-and-forth by fetching up-to-date information directly within the conversation.

Can I maintain context across messages in a web-enabled AI conversation?

Yes, context-aware conversations recall prior messages from your messages array to maintain flow. You send the full conversation history to the chat endpoint, ensuring the AI generates responses based on previous context.

Do I need USDC payments to access an AI chat agent with web search?

Yes, accessing the web-enabled AI chat requires USDC payments via the x402 protocol. This payment mechanism handles secure access to the endpoint where your messages array is processed for AI-generated responses.

What is the best way to integrate live web data into interactive chat workflows?

The best way to integrate live web data into interactive chat workflows is calling a dedicated chat endpoint with a messages array. The AI agent automatically searches the web and integrates current results into its generated response.

Does this AI chat agent work for product planning and support queries?

Yes, the AI chat agent works for product planning and support queries by providing quick research chats and answering user questions with live data. It uses web search to ensure the information returned is current and relevant.