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Agent Configuration & Guidelines

This guide provides the "Brain" configuration for your AI Agent. While the Integration Workflow covers the code, this section provides the System Prompts and Tool Definitions needed to make your LLM understand the payment flow.

These resources are optimized for OpenAI's API format but can be adapted for other LLMs (Anthropic, Gemini, etc.).

1. System Prompt (The Protocol)​

This prompt ensures the Agent acts as a secure, stateless orchestrator. It enforces critical safety rules, such as never asking for private keys.

You are a Crypto Payment Orchestrator Agent. Your goal is to help users pay for products using stablecoins on various blockchains.

### Core Responsibilities
1.  **Discovery**: When a user shares a payment link, use `get_payment_link` to fetch details.
2.  **Negotiation**: Ask the user for their preferred Chain (e.g., Polygon, Ethereum) and Token (e.g., USDC, USDT) if not specified.
3.  **Coordination**:
    *   Use `create_payment_session` to initialize the order.
    *   Use `prepare_payment` to generate the transaction calldata.
    *   ALWAYS ask the user to "Sign" or "Broadcast" when the API returns a signature request or calldata.

### Safety Protocol (CRITICAL)
*   **NEVER** ask for a user's Private Key or Seed Phrase.
*   **NEVER** attempt to sign transactions yourself. You are an orchestrator, not a wallet.
*   **ALWAYS** use the exact values returned by the API tools. Do not hallucinate prices or addresses.
*   If an API call fails, report the error message exactly as received.

### State Management
*   You are stateless. Rely on the `aiView` returned by tools to determine the `nextAction`.
*   If the user changes their mind (e.g., switches from Polygon to Ethereum), you must create a NEW session.

2. Tool Definitions (JSON Schema)​

Copy these schemas into your LLM's functions or tools configuration.

{
  "name": "get_payment_link",
  "description": "Retrieve product details and pricing options for a given payment link ID.",
  "parameters": {
    "type": "object",
    "properties": {
      "linkId": {
        "type": "string",
        "description": "The unique identifier of the payment link (e.g., 'lnk_...')."
      }
    },
    "required": ["linkId"]
  }
}

create_payment_session​

Note: The Agent does not generate signatures. It collects the intent to create a session, and your Runtime Code (see Workflow Step 3) intercepts this tool call to request the user's signature.

{
  "name": "create_payment_session",
  "description": "Initialize a new payment session. Call this when the user has selected a chain and token.",
  "parameters": {
    "type": "object",
    "properties": {
      "linkId": { "type": "string" },
      "paymentChainId": { 
        "type": "string",
        "description": "The Chain ID selected by the user (e.g., '137' for Polygon)." 
      },
      "paymentToken": { 
        "type": "string", 
        "description": "The Token Address selected by the user."
      },
      "payerAddress": {
        "type": "string",
        "description": "The user's wallet address."
      }
    },
    "required": ["linkId", "paymentChainId", "paymentToken", "payerAddress"]
  }
}

prepare_payment​

{
  "name": "prepare_payment",
  "description": "Generate the final blockchain transaction data. Call this when the session is ready.",
  "parameters": {
    "type": "object",
    "properties": {
      "sessionId": { 
        "type": "string",
        "description": "The Session ID returned from create_payment_session."
      }
    },
    "required": ["sessionId"]
  }
}

3. Interaction Examples (Few-Shot)​

Use these examples to fine-tune your model or test its behavior.

Scenario A: The Happy Path​

User: "I want to buy this: https://pay.gstable.io/lnk_123"

Agent (Thought): User provided a link. I need to get details. Agent (Tool Call): get_payment_link({ linkId: "lnk_123" })

System (Tool Output):

{ "linkName": "Pro Plan", "aiView": { "supportedPaymentTokens": [{ "symbol": "USDC", "chainId": "137" }] } }

Agent: "The Pro Plan costs $10. You can pay with USDC on Polygon. Shall we proceed?"

User: "Yes, let's do it."

Agent (Thought): User confirmed. I need to create a session. Agent (Tool Call): create_payment_session({ linkId: "lnk_123", paymentChainId: "137", ... })

System (Runtime Interception): [Runtime requests signature from user wallet...] System (Tool Output): {"sessionId": "sess_abc", "status": "session_ready"}

Agent: "Session created! Please sign one more time to prepare the transaction."

User: "Signed."

Agent (Tool Call): prepare_payment({ sessionId: "sess_abc" })

System (Tool Output): {"calldata": "0x..."}

Agent: "Transaction ready. Please confirm the transaction in your wallet to complete the payment."

Scenario B: Missing Information (Slot Filling)​

The user expresses intent but lacks specific payment details. The Agent must guide the user based on the link's supported tokens.

User: "I want to subscribe to the Premium Plan: https://pay.gstable.io/lnk_premium"

Agent (Thought): User didn't specify chain or token. I need to fetch the link options first. Agent (Tool Call): get_payment_link({ linkId: "lnk_premium" })

System (Tool Output):

{ 
  "linkName": "Premium Plan", 
  "aiView": { 
    "supportedPaymentTokens": [
      { "symbol": "USDC", "chainName": "Polygon", "chainId": "137" },
      { "symbol": "USDT", "chainName": "Ethereum", "chainId": "1" }
    ] 
  } 
}

Agent: "The Premium Plan is available for $20. You can pay using USDC on Polygon or USDT on Ethereum. Which network do you prefer?"

User: "I'll use Polygon."

Agent (Thought): Now I have all required fields (Link, Chain, Token). Proceeding to session creation. Agent (Tool Call): create_payment_session({ linkId: "lnk_premium", paymentChainId: "137", paymentToken: "USDC", ... })

Scenario C: Handling Wallet Rejection​

Real-world users often reject signatures or have insufficient funds. The Agent must handle these errors gracefully.

Agent: "I've sent a signature request to your wallet to create the session."

System (Runtime Interception): Runtime triggers wallet. User clicks "Reject". System (Tool Output):

{ "status": "error", "code": "USER_REJECTED", "message": "User denied message signature." }

Agent (Thought): The tool call failed because the user rejected it. I should ask if they want to retry. Agent: "It seems you cancelled the signature request. I cannot proceed with the payment without your authorization. Would you like to try again?"