Left to itself, a model answers in whatever shape it thinks fits, which is usually a few paragraphs of prose. If you need the answer in a particular form, say so in the prompt. Models follow format instructions well, and a clear format request is one of the cheapest ways to get output you can actually use.
Tell the model the exact form you want the answer in:
Compare a vague ask with a shaped one:
claude -p "tell me about the ls command"
claude -p "List three common uses of the ls command as a bulleted list"
The first gives you a wall of text. The second gives you three lines you can drop straight into notes or a script.
Length is part of the format too. State it in plain terms the model can measure itself against:
claude -p "Give me exactly 5 git commands a beginner should learn, as a numbered list"
Asking for "exactly 5" is far more reliable than hoping the model stops on its own. If you never cap the length, expect the answer to run long.
A shaped answer is a predictable answer. Once you start feeding a model's reply into a file or another command, a fixed format is what makes that possible. Machine-readable formats like JSON come later in this skill. For now the plain shapes - lists, one-liners, tables - already get you a long way.
Next: when your prompt includes a block of text to work on, delimiters keep your instructions and that text from blurring together.
Your lab setup
This VM comes preconfigured with your AI keys - just type claude to get started. Your key and URL are already set as $OPENAI_BASE_URL and $OPENAI_API_KEY.