The essential loop

Stripped to its core, every agent loop is:

messages = [system_prompt, ...history, user_message]
repeat up to N times:
    response = model.call(messages, tools)
    if response has no tool calls:
        return response.text          # the model is done
    results = run(response.tool_calls)  # execute the actions
    messages.append(response)           # record what the model did
    messages.append(results)            # record what the tools returned

That's it. The model is given the conversation and the tool catalog; it either answers or asks for tools; if it asks, you run them, append both the request and the results, and call again. The loop ends when the model answers without requesting tools (or a cap is hit).

This simple structure is deceptively powerful: by chaining tool calls, the model can read a file, use what it learned to search an API, use those results to draft a document, and finally summarise, all from a single user message, with the loop carrying it through.