Few-Shot Example Designer
Create a few-shot prompt for teaching an LLM to [task]
Prompt
Create a few-shot prompt for teaching an LLM to [task]. Design 5 high-quality input-output examples that: (1) Cover the full range of input variation. (2) Demonstrate edge cases in examples 4-5. (3) Show consistent output format. (4) Implicitly teach the underlying pattern without stating it. (5) Are ordered from simple to complex. After the examples, write the final task prompt. Explain: why you chose these specific examples and what pattern they collectively teach.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Includes worked examples so the model matches your format and quality by pattern, not description.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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