monetize-guide

Monetize Guide

Step-by-step guide to expose local GPU resources or HTTP services as x402 payment-gated endpoints with on-chain discovery via ERC-8004.

When to Use

• User says "monetize my machine", "sell my GPU", or "expose my service for payments"
• Setting up a new paid endpoint from scratch
• Need to figure out what to sell and at what price

When NOT to Use

• Managing existing offers (list/status/delete) — use sell directly
• Buying inference from others — use buy-x402
• Cluster diagnostics — use obol-stack

Workflow

Follow these phases in order. Stop and ask the user for confirmation before executing phase 4.

Phase 1: Pre-flight Checks

Verify the environment is ready before proceeding.

# 1. Check cluster is running
obol kubectl get nodes

# 2. Check the agent is initialized (has RBAC for monetization)
obol kubectl get clusterrolebinding openclaw-monetize-read-binding -o jsonpath='{.subjects}'

# 3. Get the wallet address (auto-generated by agent)
python3 ${OBOL_SKILLS_DIR:-/data/.openclaw/skills}/ethereum-local-wallet/scripts/signer.py accounts

If cluster is not running: Tell the user to run obol stack up first. Do NOT run it yourself — it takes several minutes and changes system state.

If agent has no RBAC subjects: Tell the user to run obol agent init.

If no wallet address: The wallet is created during obol stack up. If missing, the stack may not have completed setup.

Phase 2: Detect What Can Be Sold

For GPU / Inference

# Check what Ollama models are available locally
curl -s http://localhost:11434/api/tags | python3 -c "
import json, sys
data = json.load(sys.stdin)
for m in data.get('models', []):
    size_gb = m.get('size', 0) / 1e9
    print(f\"  {m['name']:30s} {size_gb:.1f} GB\")
"

Report the available models to the user. If no models are found, suggest they pull one:

ollama pull qwen3.5:4b    # Smallest current Qwen, ~3.4 GB (low-RAM laptops)
ollama pull qwen3.5:9b    # Validated baseline, ~6.6 GB
ollama pull qwen3.6:27b   # High quality, ~17 GB (needs ≥32GB RAM)