Guidance for System Prompt Documents
Quality criteria and best practices for creating excellent system prompt documents that integrate Persona, Purpose, and Protocol using the PPP framework
Explore
597 skills indexed with the new KISS metadata standard.
Quality criteria and best practices for creating excellent system prompt documents that integrate Persona, Purpose, and Protocol using the PPP framework
Here is an example conversation where your expected responses are in the "FDAi Agent" property and the human input statements are in slash comments.
Here is an example conversation where your expected responses are in the "FDAi Agent" property and the human input statements are in slash comments.
You simply provide a description and retrieve the original prompt that Dall.E sent to ChatGPT for a response.
You simply provide a description and retrieve the original prompt that Dall.E sent to ChatGPT for a response.
You simply provide a description and retrieve the original prompt that Dall.E sent to ChatGPT for a response.
Large language models can actually be excellent at both ideating and creating and improving system prompts written for other AI tools. One of the pitfalls of using this approach, however, is that sometimes even with careful parameter setting, the models actually take the system prompts as your own i
Here is an example conversation where your expected responses are in the "FDAi Agent" property and the human input statements are in slash comments.
You simply provide a description and retrieve the original prompt that Dall.E sent to ChatGPT for a response.
Track and evaluate AI predictions over time to assess accuracy. Use when reviewing past predictions to determine if they came true, failed, or remain uncertain.
Operating model for tracking, attributing, and accelerating partner-sourced
R 语言常用方法
<script >
Name | Type | Description | Notes
An characters can have skills, skill can be buff skill, nerf skill, attack skill or may mix all of them as you wish
| データベース| JSONファイル | 大域変数 | オブジェクト |
globs:
This is a modern Pakistani tax calculation application with:
file_location: root_directory
- **Project**: The AI Orchestrator - AI-Augmented Full-Stack Engineering Bootcamp
"model": "DeepCORO_CLIP",
This project uses a custom Logger class instead of `print()` and `debugPrint()` statements. The logger provides structured, categorized, and colorized logging with different levels and categories.
- The application name is "LLM-2000"
This is for a bootstrapped startup.