USB-C for Agents

The agent is only as good as its tools.

You ship production systems. You are new to agents. And the agent that aced every demo just went live and called the refund tool with a customer's order ID in the amount field. It passes garbage arguments, loops on an error it cannot read, and burns ten thousand tokens on work one function should have handled. You blame the model. It was never the model.

A huge fraction of agent quality lives in the layer most engineers treat as plumbing: the tools you expose and the way you describe them. USB-C for Agents treats that layer as the product. Get it right and an average model becomes a reliable agent. Get it wrong and no frontier model will save you.

A hands-on function calling and tool use guide for engineers who ship to production:

• Function calling from the wire up: how tool use actually works, why MCP, the Model Context Protocol, won as the open standard, and what an MCP server done right looks like.
• A tool description is a user interface that happens to be read by a model. Learn to write the ones that end garbage arguments.
• Designing tools for LLM agents that survive loops and retries, with honest error feedback the agent can actually act on.
• Sandboxed code execution that cuts agent token costs by orders of magnitude on measured workloads.
• First-call tool-success rate, the recurring metric that tells you whether the connection improved, not just the model.
• Trust you can ship: audit trails, provenance, and an autonomy slider, plus the tradeoff faced head-on, since every guardrail that makes a tool safe also narrows what the agent may do alone.

Written by an engineer learning this frontier in the open against retail-scale systems, APIs, and messy data. Read it and you will stop tuning prompts and start engineering the connection, turn integration from afterthought into your unfair advantage, and build AI agents that work on the first call. Reliable agent quality is integration engineering, not model magic.

For backend and platform engineers exposing real systems, APIs, and data to AI agents. Part of the Build Agents You Can Trust series, in The Verifier's Library.