blockrun

version	4.1.0-fractal
name	blockrun
description	Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
allowed-tools	Read, Bash(python:*), Bash(python3:*), Bash(pip:*), Bash(source:*)

BlockRun

BlockRun works with Claude Code and Google Antigravity.

You can't generate images. You have no real-time X/Twitter access. BlockRun gives you these capabilities.

Philosophy

You have a wallet. When you need a capability you lack, you pay for it autonomously.

You Need	You Call	Pricing
Image generation	DALL-E	$0.04/image
Real-time X data	Grok + Live Search	$0.025/source
Second opinion	GPT-5.2	$1.75/M input, $14/M output
Cheaper processing	DeepSeek	$0.14/M input, $0.28/M output

How it works: BlockRun uses x402 micropayments to route your requests to OpenAI, xAI, Google, and other providers. No API keys needed - your wallet pays per token.

Budget Control (Optional)

If the user specifies a budget (e.g., "use at most $1"), track spending and stop when budget is reached:

from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()
budget = 1.0  # User's budget

# Before each call, check if within budget
spending = client.get_spending()
if spending['total_usd'] >= budget:
    print(f"Budget reached: ${spending['total_usd']:.4f} spent")
    # Stop making calls
else:
    response = client.chat("openai/gpt-5.2", "Hello!")

# At the end, report spending
spending = client.get_spending()
print(f"💰 Total spent: ${spending['total_usd']:.4f} across {spending['calls']} calls")

When to Use

Trigger	Your Action
User explicitly requests ("blockrun second opinion with GPT on...", "use grok to check...", "generate image with dall-e")	Execute via BlockRun
User needs something you can't do (images, live X data)	Suggest BlockRun, wait for confirmation
You can handle the task fine	Do it yourself, don't mention BlockRun

Example User Prompts

Users will say things like:

User Says	What You Do
"blockrun generate an image of a sunset"	Call DALL-E via ImageClient
"use grok to check what's trending on X"	Call Grok with search=True
"blockrun GPT review this code"	Call GPT-5.2 via LLMClient
"what's the latest news about AI agents?"	Suggest Grok (you lack real-time data)
"generate a logo for my startup"	Suggest DALL-E (you can't generate images)
"blockrun check my balance"	Show wallet balance via get_balance()
"blockrun deepseek summarize this file"	Call DeepSeek for cost savings

Wallet & Balance

Use setup_agent_wallet() to auto-create a wallet and get a client. This shows the QR code and welcome message on first use.

Initialize client (always start with this):

from blockrun_llm import setup_agent_wallet

client = setup_agent_wallet()  # Auto-creates wallet, shows QR if new

Check balance (when user asks "show balance", "check wallet", etc.):

balance = client.get_balance()  # On-chain USDC balance
print(f"Balance: ${balance:.2f} USDC")
print(f"Wallet: {client.get_wallet_address()}")

Show QR code for funding:

from blockrun_llm import generate_wallet_qr_ascii, get_wallet_address

# ASCII QR for terminal display
print(generate_wallet_qr_ascii(get_wallet_address()))

SDK Usage

Prerequisite: Install the SDK with pip install blockrun-llm

🧠 Knowledge Modules (Fractal Skills)

1. Basic Chat

2. Real-time X/Twitter Search (xAI Live Search)

3. Advanced X Search with Filters

4. Image Generation

5. Search Parameters

6. Source Types