PromptsLabs

PromptsLabs – AI Prompt Library for LLM Testing (Prompts Labs) is an online repository and community-driven collection of prompts designed to help you test and evaluate large language models (LLMs). It provides copy-paste prompts contributed by the community, the ability to add your own prompts, and ready-to-use examples to benchmark model behavior across various scenarios. The platform emphasizes practical testing, quick access to prompts, and collaboration among users to explore model performance on diverse tasks.

How to Use PromptsLabs

1. Browse or search prompts. Explore the library or use the search to find prompts that fit your testing needs.
2. Copy and run prompts. Copy the prompt text and run it against your preferred LLM or testing environment.
3. Review expected outputs. Compare the model’s response to the provided expected output to gauge performance and behavior.
4. Submit or request prompts. If you have a new prompt or need a template, submit it to the community for others to use.

Typical Prompts and Examples

• Hot Prompt: How many R's are in the word strawberry? Expected Output: 3
• Maze Prompt 2: Prompt: I have 3 apples today. I ate one yesterday. How many do I have left today? Expected Output: You have 3 apples today. Eating one yesterday doesn’t change that for today.
• Maze Prompt 3: Prompt: Compare 9.9 and 9.11--which is the largest number? Expected Output: 9.9 is larger because in decimal comparisons, you check digits from left to right. At the tenths place (first decimal), 9 is greater than 1, so 9.9 > 9.11.

What It Covers

• A library of prompts for testing diverse capabilities of LLMs (reasoning, math, comprehension, pattern recognition, etc.).
• Community-contributed prompts and the ability to create your own prompts.
• Quick, copy-paste access for fast experimentation.
• Organized prompts such as “Hot Prompt” and “Maze Prompt” series to benchmark specific tasks.

How It Works

• Browse prompts or request new ones.
• Copy prompts into your testing environment and run them against your chosen LLM.
• Compare model outputs with expected results to assess accuracy and behavior.

Safety and Ethical Considerations

• Use prompts for ethical, educational, and research purposes. Respect terms and conditions and avoid using prompts to manipulate or mislead models in harmful ways.

Core Features

• Community-driven library of LLM testing prompts
• Copy-paste prompts for quick experiments
• Ability to submit and share your own prompts
• Ready-made prompt categories and example sets (e.g., Hot Prompts, Maze Prompts)
• Clear expected outputs to facilitate benchmarking
• GitHub-hosted codebase and project history for transparency