few-shot-prompting

What problem does it solve?

Few-shot prompting dramatically improves LLM output quality and consistency by providing 2-8 examples of the desired input→output behavior, enabling rapid task teaching without fine-tuning.

Core Features & Use Cases

• Basic Few-Shot Template: provide a minimal template to shape task behavior.
• JSON Output Few-Shot: enforce structured outputs like JSON.
• Code Transformation Few-Shot: help convert code styles or patterns.
• Example Selection Guidelines: guidance on choosing diverse, edge-case examples.
• Chain-of-Thought Few-Shot: includes reasoning traces in examples for complex tasks.
• Evaluation & Guardrails: checks for correctness and consistency.

Quick Start

Create a prompt with 3-5 representative examples and a clearly defined output format, then test on real inputs.