
Blockrun
Let your coding agent pay per use for images, live X data, and alternate LLMs without managing separate API keys.
Overview
BlockRun is an agent skill for the Build phase that lets Claude Code and Antigravity autonomously pay for images, live X data, and routed LLM calls via x402 micropayments.
Install
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill blockrunWhat is this skill?
- Routes agent calls to DALL-E, Grok live search, GPT-5.2, and DeepSeek with listed per-token or per-image pricing
- Uses x402 micropayments and an agent wallet so you skip per-provider API key setup
- Optional budget cap via get_spending() checks before each client.chat() call
- Documented for Claude Code and Google Antigravity
- Covers capability gaps like image generation and real-time X/Twitter data from inside the agent
- Pricing table lists DALL-E at $0.04/image and Grok live search at $0.025/source
- Documents four routed capability types: images, X data, GPT-5.2, and DeepSeek
Adoption & trust: 452 installs on skills.sh; 40.1k GitHub stars; 0/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your agent cannot generate images or fetch real-time X data and you do not want to wire and rotate API keys for every provider yourself.
Who is it for?
Solo builders extending Claude Code or Antigravity with on-demand paid capabilities during agent integration sprints.
Skip if: Teams that need fixed enterprise API contracts, full offline workflows, or build tasks with no external model or media calls.
When should I use this skill?
When the agent lacks image generation, real-time X access, or you want to route to priced external LLMs via BlockRun wallet.
What do I get? / Deliverables
Your agent can call priced external capabilities through a funded wallet with optional budget enforcement and a spending summary when the run finishes.
- External API calls completed via BlockRun client with spending report
Recommended Skills
Journey fit
BlockRun is installed when you are building agent workflows and need external capabilities wired into Claude Code or Antigravity during implementation. It sits on integrations because it routes agent requests to third-party providers via x402 micropayments rather than owning app UI or backend domain logic.
How it compares
Use this integration skill instead of hard-coding separate OpenAI, xAI, and image API clients with manual key management.
Common Questions / FAQ
Who is blockrun for?
BlockRun is for solo and indie builders running Claude Code or Google Antigravity who want agents to buy missing capabilities (images, live X search, alternate LLMs) per use from a wallet.
When should I use blockrun?
Use BlockRun in the Build phase when wiring agent-tooling or integrations—any time the agent needs DALL-E, Grok live search, GPT-5.2, or DeepSeek mid-task and you prefer micropayments over API keys.
Is blockrun safe to install?
BlockRun moves real money through an agent wallet and external providers; review the Security Audits panel on this Prism page and set explicit budgets before enabling autonomous spending.
SKILL.md
READMESKILL.md - Blockrun
# 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: ```python 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):** ```python 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.):** ```python 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:** ```python 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` ### Basic Chat ```python from blockrun_llm import setup_agent_wallet client = setup_agent_wallet() # Auto-creates wallet if needed response = client.chat("openai/gpt-5.2", "What is 2+2?") print(response) # Check spending spending = client.get_spending() print(f"Spent ${spending['total_usd']:.4f}") ``` ### Real-time X/Twitter Search (xAI Live Search) **IMPORTANT:** For real-time X/Twitter data, you MUST enable Live Search with `search=True` or `search_parameters`. ```python from blockrun_llm import setup_agent_wallet client = setup_agent_w