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Circle Products & Developer Toolings

From Prompt to Deployment with Circle Skills and Vercel Skills

 ecosystem for building on Arc Testnet. While the original guide highlights powerful pro-tier tools like Claude Code, I wanted to explore if we could achieve the exact same prompt-to-deployment pipeline using a 100% free, open-source stack.

Here is my experience building an Arc Checkout MVP using free LLM APIs, along with some workflow and security practices for the community.

if the product is free, your data might be the currency. Granting an autonomous AI agent full read/write access to a primary local machine introduces unnecessary security risks.

To build safely, I deployed a budget Linux VPS. This sandboxed environment allowed me to experiment with 

 (a CLI coding agent) paired with open-source and preview models: 

, it successfully generated a stateless Next.js checkout interface. The agent correctly implemented the 6-decimal ERC-20 standard for USDC and properly configured the Arc Testnet chain ID (5042002) to ensure accurate gas estimation in Wagmi/Viem.

(Note: For testing, payments are routed to one of the top active accounts from testnet.arcscan.app/accounts to ensure a valid onchain recipient).

https://arc-tip-jegt46osj-kamika.vercel.app/

If you are integrating CLI agents with Arc infrastructure, here are a few practical takeaways:

:  Don't let models burn API limits on recursive framework errors. Use 

 to wipe bloated context, then explicitly load 

 into the context window. This forces the agent to rely on Circle’s procedural documentation rather than its outdated pre-training data.

:  Before asking the agent to execute a massive architectural refactor, simply duplicate the project directory. Rolling back a folder is vastly more efficient than prompting an LLM to undo its own syntax errors.

The current live site is an MVP. However, if the community finds this lightweight checkout tool useful, let me know! I’d be happy to refine the design and add a dropdown list of selectable testnet addresses for easier QA.

 framework is remarkably resilient, even with lightweight free models, provided you supply the right context. Build safely, sandbox your environments, and deploy on Arc.

Building on Arc Testnet: Zero-Cost Agentic Workflows and Sandboxing

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