The Four Pieces of a Useful Prompt: Task, Context, Constraints, and Output

I do not keep a giant prompt template for everything. I keep four questions. They help me explain the job without piling on rules that do not matter. If output shape matters more than prose, Structured Outputs: When a Schema Beats More Prompt Words shows when a schema is the better tool.

Start with a verb: explain, compare, classify, draft, review, or generate. “Help me with this” does not say what the model should do. “Review this bug report and list the missing information needed to reproduce it” does.

Context is not every fact you know. It is the information that affects the task. For a coding review, it might be the language, current behavior, expected behavior, and the actual code. For a game design idea, it might be platform, player count, and the mechanic you want to prototype. Do not paste a whole repository when a ten-line function is enough.

Constraints can be a time limit, a library restriction, an audience, a source boundary, or a safety rule. Keep them relevant. “Do not use third-party packages” matters if you need a standard-library solution. “Be amazing and creative” usually does not help the model meet a measurable requirement.

If I need a checklist, ask for one. If I need code plus tests, say that. If I need structured data, specify the fields. For application integrations, do not rely on prompt words alone when a provider supports schema-based output. Google’s Gemini structured-output documentation and OpenAI’s structured-output guidance explain why API-level constraints can be preferable for machine-readable results.

Here is a vague request: Give me ideas for a game. Here is a version I can actually evaluate: Task: Propose three mechanics for a two-player cooperative puzzle game. Context: Both players can see different parts of the same map; neither can solve a room alone. Constraints: Each mechanic must be prototype-able with paper cards in one afternoon. Avoid combat and long dialogue. Output: For each idea, give the player action, the moment of cooperation, one failure mode, and a 10-minute paper test. The better prompt does not guarantee great ideas. It gives me a way to reject weak ones. If one mechanic cannot be paper-tested in an afternoon, it fails the stated constraint. If the ideas are too similar, I can ask for a revision that varies the cooperation pattern. My criterion guides the next prompt.

Not every prompt needs all four parts written as headings. For a simple translation, “Translate this paragraph into Spanish and preserve the tone” may be enough. Add more only if it changes the result or helps you test it. The framework is a check against missing information, not a demand to write a page of instructions. When in doubt, ask: “If I remove this sentence, would a good answer change?” If not, consider removing it. If yes, keep it.

Rewrite one vague prompt you use often. Put the four parts on separate lines. Run it, then deliberately remove one part and compare the outputs against the same test. You will discover which part mattered for that task. Save the leanest prompt that still passes. Keep learning: Use Constraints Without Boxing the Model Into Nonsense, Structured Outputs: When a Schema Beats More Prompt Words, and What to Put in a Reusable Prompt Template.