On XML interception, enforcement prompts, and the architecture of agency
The Problem with Uncensored Models
Uncensored models are the ones you actually want for agentic work. They'll follow complex multi-step instructions without second-guessing. They won't refuse reasonable tasks because a safety classifier got nervous. They'll write the dark stuff and the weird stuff and the stuff that makes corporate compliance teams break out in hives. If you're building an autonomous agent that needs to operate in the real world — generating content, executing code, making decisions with real consequences — you need a model that doesn't flinch.
But there's a problem. Uncensored models often can't do native function calling.
The OpenAI-compatible tools parameter in the chat completions API is the standard way to give a language model structured capabilities. You pass a JSON schema describing each available tool. The model decides when to use one and returns a tool_calls array in its response. Your code executes the tool, feeds the result back, and the conversation continues. It's clean. It's standardized. It works beautifully for GPT-4, Claude, and the other frontier models that were explicitly trained to use it.
