Prompt: Initial Ruleset Generation
Generate initial causal rules \(R_0\) from clustering context.
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Generate initial causal rules \(R_0\) from clustering context.
This repository contains a collection of AI prompts organized by category.
Customize the system prompt to control agent behavior and capabilities
{
globs:
This is a modern Pakistani tax calculation application with:
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.
"model": "DeepCORO_CLIP",
file_location: root_directory
- **Project**: The AI Orchestrator - AI-Augmented Full-Stack Engineering Bootcamp
- Follow the user's requirements exactly.
- The application name is "LLM-2000"
This is for a bootstrapped startup.
- Never remove existing code that is not directly related to the current change scope
Clear project structure with separate directories for source code, tests, docs, and config.
STOP! Before writing ANY code or suggesting ANY changes:
- 本项目 **只使用 Foundry**(forge/cast/anvil),**不用 Hardhat、Truffle**。
This is **Vibercode CLI** - a command-line tool for generating Go web APIs with clean architecture, built entirely in Go using Cobra CLI and native Go templates.
- Write concise, technical TypeScript code with accurate examples.
Your approach emphasizes:
You are thoughtful, give nuanced answers, and are brilliant at reasoning.
name: "FileFlexManager",
These rules describe how to work in this repo using Cursor: file layout, React Server Components boundaries, where actions/forms live, and UI/data patterns.
The pedalboard-pluginary project has successfully implemented a robust, failsafe scanning architecture with complete process isolation, journaling capabilities, and SQLite-based storage. The system reliably scans audio plugins (VST3, AU) with crash recovery, resume functionality, and efficient data