What is few-shot prompting?

Few-shot prompting gives a model a handful of worked examples (input paired with the desired output) before the real request. The examples demonstrate the format, tone and reasoning you want, letting the model imitate them without any fine-tuning. It is one of the most reliable ways to steer output quality.

How many examples should I include?

Two to five examples is a common sweet spot. Too few and the model may not infer the pattern; too many wastes context and tokens. Make sure your examples are diverse and cover edge cases rather than repeating the same shape.

What is the difference between the OpenAI and Anthropic formats?

The OpenAI style alternates user and assistant role messages, which you place in the messages array. The Anthropic style wraps each example in XML tags such as example, input and output inside a single prompt, which Claude parses cleanly. Both teach the same pattern — pick the one that matches your API call.

Are my examples uploaded anywhere?

No. The builder formats everything locally in your browser using JavaScript. Your example text is never sent to a server, so it is safe for proprietary or sensitive content.

Should examples come before or after the instruction?

Put your instruction first, then the few-shot examples, then the real input last. The model reads top to bottom, so the most recent thing it sees should be the actual task it must complete in the demonstrated style.

Few-Shot Example Builder

Few-shot examples are the single most effective lever for shaping LLM output without fine-tuning. This builder lets you enter clean input/output pairs in a form and exports them in the exact format your API expects — OpenAI message arrays, Anthropic XML, or a generic layout.

How it works

Add one row per example: the representative input and the ideal output you want the model to learn from. Pick a target format and the tool assembles a consistent, copy-ready block:

OpenAI — alternating user / assistant role messages for the messages array.
Anthropic — <example> blocks with <input> and <output> tags for Claude.
Generic — plain Input: / Output: pairs that work in any prompt.

All formatting happens locally. Nothing you type is uploaded.

Tips and examples

Keep examples diverse — cover the easy case, a tricky edge case and the failure mode you want the model to avoid. Two to five examples is usually enough; beyond that you spend tokens for diminishing returns. Place the examples after your instruction and before the real user input so the model sees the task it must complete last. If output formatting matters (JSON, a specific schema), make every example’s output strictly conform — the model copies whatever it sees.