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Agentic Commerce Toolkit

End-to-end agentic commerce workflow using Lightning Network. Use when an agent needs to set up a full payment stack (lnd + lnget + aperture), buy or sell data via L402, or enable agent-to-agent micropayments.

Installable skillAGPL-3.0-onlyBy jiayaoqijiaUpdated Nov 2, 2026
INTENDED FOROpenClawInstall in a listed agent.

instructions.md

---
name: commerce-7b8184b11d5e
description: End-to-end agentic commerce workflow using Lightning Network. Use when an agent needs to set up a full payment stack (lnd + lnget + aperture), buy or sell data via L402, or enable agent-to-agent micropayments.
user-invocable: false
---

# Agentic Commerce Toolkit

This plugin provides a complete toolkit for agent-driven Lightning Network
commerce. Three skills work together to enable agents to send and receive
micropayments over the Lightning Network using the L402 protocol.

## Components

| Skill | Purpose |
|-------|---------|
| **lnd** | Run Lightning Terminal (litd: lnd + loop + pool + tapd) |
| **lnget** | Fetch L402-protected resources (pay for data) |
| **aperture** | Host paid API endpoints (sell data) |

## Full Setup Workflow

### Step 1: Install All Components

```bash
# Install litd (Lightning Terminal — bundles lnd + loop + pool + tapd)
skills/lnd/scripts/install.sh

# Install lnget (Lightning HTTP client)
skills/lnget/scripts/install.sh

# Install aperture (L402 reverse proxy)
skills/aperture/scripts/install.sh
```

### Step 2: Set Up the Lightning Node

```bash
# Start litd container (testnet by default)
skills/lnd/scripts/start-lnd.sh

# Create an encrypted wallet
skills/lnd/scripts/create-wallet.sh --mode standalone

# Verify node is running
skills/lnd/scripts/lncli.sh getinfo
```

### Step 3: Fund the Wallet

```bash
# Generate a Bitcoin address
skills/lnd/scripts/lncli.sh newaddress p2tr

# Send BTC to this address from an exchange or another wallet

# Verify balance
skills/lnd/scripts/lncli.sh walletbalance
```

### Step 4: Open a Channel

```bash
# Connect to a well-connected node (e.g., ACINQ, Bitfinex)
skills/lnd/scripts/lncli.sh connect <pubkey>@<host>:9735

# Open a channel
skills/lnd/scripts/lncli.sh openchannel --node_key=<pubkey> --local_amt=1000000

# Wait for channel to confirm (6 blocks)
skills/lnd/scripts/lncli.sh listchannels
```

### Step 5: Configure lnget

```bash
# Initialize lnget config (auto-detects local lnd)
lnget config init

# Verify connection
lnget ln status
```

### Step 6: Fetch Paid Resources

```bash
# Fetch an L402-protected resource
lnget --max-cost 1000 https://api.example.com/paid-data

# Preview without paying
lnget --no-pay https://api.example.com/paid-data

# Check cached tokens
lnget tokens list
```

### Step 7: Host Paid Endpoints (Optional)

```bash
# Start your backend service
python3 -m http.server 8080 &

# Configure aperture to protect it
skills/aperture/scripts/setup.sh --insecure --port 8081

# Start the L402 paywall
skills/aperture/scripts/start.sh

# Other agents can now pay to access your endpoints
# lnget --max-cost 100 https://your-host:8081/api/data
```

## Agent-to-Agent Commerce

The full loop for autonomous agent commerce:

```
Agent A (buyer)                    Agent B (seller)
─────────────                      ─────────────
lnd node running                   lnd node running
  ↓                                  ↓
lnget fetches URL ──────────────→ aperture receives request
                                     ↓
                                   Returns 402 + invoice
  ↓
lnget pays invoice ─────────────→ lnd receives payment
  ↓                                  ↓
lnget retries with token ───────→ aperture validates token
                                     ↓
                                   Proxies to backend
  ↓                                  ↓
Agent A receives data ←──────────  Backend returns data
```

### Buyer Agent Setup

```bash
# One-time setup
skills/lnd/scripts/install.sh
skills/lnget/scripts/install.sh
skills/lnd/scripts/start-lnd.sh
skills/lnd/scripts/create-wallet.sh --mode standalone
lnget config init

# Fund wallet and open channels (one-time)
skills/lnd/scripts/lncli.sh newaddress p2tr
# ... send BTC ...
skills/lnd/scripts/lncli.sh openchannel --node_key=<pubkey> --local_amt=500000

# Ongoing: fetch paid resources
lnget --max-cost 100 -q https://seller-api.example.com/api/data | jq .
```

### Seller Agent Setup

```bash
# One-time setup
skills/lnd/scripts/install.sh
skills/aperture/scripts/install.sh
skills/lnd/scripts/start-lnd.sh
skills/lnd/scripts/create-wallet.sh --mode standalone

# Configure and start paywall
skills/aperture/scripts/setup.sh --port 8081 --insecure

# Start backend with content to sell
mkdir -p /tmp/api-data
echo '{"market_data": "..."}' > /tmp/api-data/data.json
cd /tmp/api-data && python3 -m http.server 8080 &

# Start aperture
skills/aperture/scripts/start.sh

# Buyers can now access:
# https://your-host:8081/api/data.json (100 sats per request)
```

## Cost Management

Agents should always control spending:

```bash
# Set a hard limit per request
lnget --max-cost 500 https://api.example.com/data

# Check cost before paying
lnget --no-pay --json https://api.example.com/data | jq '.invoice_amount_sat'

# Track spending via token list
lnget tokens list --json | jq '[.[] | .amount_paid_sat] | add'
```

## Security Summary

| Component | Security Model |
|-----------|---------------|
| **Wallet passphrase** | Stored at `~/.lnget/lnd/wallet-password.txt` (0600) |
| **Seed mnemonic** | Stored at `~/.lnget/lnd/seed.txt` (0600) |
| **L402 tokens** | Stored at `~/.lnget/tokens/<domain>/` per domain |
| **lnd macaroons** | Standard lnd paths at `~/.lnd/data/chain/...` |
| **Aperture DB** | SQLite at `~/.aperture/aperture.db` |

For production use with significant funds, use watch-only mode with a remote
signer container. See the `lightning-security-module` skill for details.

## Stopping Everything

```bash
skills/aperture/scripts/stop.sh
skills/lnd/scripts/stop-lnd.sh
```

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Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.