agentic-prompts

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# 🤖 AI Agent Prompts & Configurations

[![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)
[![Prompt Engineering](https://img.shields.io/badge/Topic-Prompt_Engineering-orange.svg)](#)

**A personal, curated collection of prompts, modes, and configurations for AI coding assistants.**

[Available Modes](#-available-modes) • [Available Commands](#-available-commands) • [Tools & Platforms](#️-applicable-tools--platforms) • [Architecture](#️-architecture-prompt-as-code) • [Getting Started](#-getting-started)

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## 📖 Overview

Welcome to my personal, curated collection of prompts, modes, and configurations for AI coding assistants. This repository is designed for anyone interested in **Prompt Engineering**, customizing **AI Agents**, or enhancing their workflow with Large Language Models (LLMs).

This collection contains ready-to-use templates for defining agent personas, delegating tasks, and structuring interactions with various AI tools.

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## 🎭 Available Modes

This repository provides the following agent modes, forming the "Pantheon" team:

| Mode | Description |
|------|-------------|
| **🧠 Maestro** | An expert project orchestrator who decomposes complex tasks, delegates them to specialist agents, and manages the overall project plan. |
| **🏛️ Principal Engineer** | A top-tier technical leader for deep system analysis, architectural design, and long-term strategic planning. |
| **💻 Lead Implementer** | An expert developer who translates architectural plans into clean, efficient, and maintainable application code. |
| **🧪 Test Engineer** | A dedicated quality expert who writes clean, fast, and reliable unit and integration tests to ensure code correctness and robustness. |
| **🎭 Advocate** | A user experience specialist who designs intuitive, enjoyable, and habit-forming user flows by applying principles of usability and psychology. |
| **🌿 Gardener** | A meticulous engineer focused on code quality, fighting entropy by refactoring, updating dependencies, and eliminating technical debt. |
| **👾 Mr. Robot** | A cybersecurity expert who performs security audits and finds unconventional, low-cost solutions by reverse-engineering and exploiting external systems. |
| **👁️ Observer** | A performance and systems expert who makes applications transparent by instrumenting code with logs, metrics, and traces, and setting up deployment infrastructure. |
| **👺 Annihilator** | A cynical but logical agent whose sole purpose is to challenge complexity and ruthlessly identify features, code, or concepts that should be removed to regain focus. |

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## ⚡ Available Commands

This repository also provides slash-commands — reusable prompt templates that can be triggered during a conversation:

| Command | Description |
|---------|-------------|
| **📦 GitHub Release** | Generates professional release notes by analyzing git commits. Extracts changes between tags and creates a structured changelog with breaking changes, new features, bug fixes, and upgrade instructions. |
| **💬 Question ChatGPT** | Prepares a well-structured question with full context for an external LLM. Useful when you need a fresh perspective from a different AI model that doesn't have access to your current conversation. |
| **🔬 Subtask Analysis** | Creates a research-focused sub-agent within the current session. The sub-agent reads files and provides detailed analysis without making any code changes. |
| **💻 Subtask Code** | Creates a code-writing sub-agent for implementing specific changes. Each sub-agent handles isolated tasks with full context, ensuring clean and focused modifications. |

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## 📝 Available Prompts

This repository also provides standalone prompts — reusable prompt templates for specific tasks:

| Prompt | Description |
|--------|-------------|
| **🗜️ Context Compression** | Compresses long conversation history into a detailed summary that preserves all important context. Used when conversation exceeds token limits. |

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## 🛠️ Applicable Tools & Platforms

The configurations in this repository are designed to be highly adaptable and can be used with a wide range of AI agent tools and platforms:

| Category | Tools |
|----------|-------|
| **IDE Extensions** | Roo Code, Cline, Kilo Code, Cursor, Windsurf, Continue |
| **Chat Platforms** | LibreChat, Open WebUI |
| **APIs & CLIs** | Anthropic Claude Code, Google Gemini, OpenAI Codex/ChatGPT, OpenCode |

> **Note:** While the principles are universal, the specific file paths and structures are optimized for **Roo Code**.

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## 🏗️ Architecture: "Prompt-as-Code"

This repository uses a **Roles Builder** system to manage agent modes. This approach treats prompt engineering as a development process, where configurations are generated from source files.

### Repository Structure

| Path | Description |
|------|-------------|
| **`/commands`** | Contains markdown templates for slash-commands (see [Available Commands](#-available-commands) above). |
| **`/prompts`** | Contains standalone prompt templates (see [Available Prompts](#-available-prompts) above). |
| **`/roles_builder`** | The source directory for agent modes. |
| ↳ `build.py` | A Python script that assembles all components into the final configuration file. |
| ↳ `manifest.yaml` | Defines which agent modes to include in the build. |
| ↳ `/sources` | Contains the raw materials (metadata and instructions) for each mode. |
| **`custom_modes.yaml`** | The **generated output file** for agent modes. This file should not be edited manually, as it is overwritten by the build script. |

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## 🚀 Getting Started

The setup process involves two distinct types of assets: **Custom Modes** and **Custom Commands**.

### 1. Custom Modes

Custom modes are managed via the Roles Builder workflow.

<details>
<summary><b>Step 1: Edit the Sources</b></summary>

All modifications to modes are done in the `/roles_builder/sources` directory.
- To change a mode's instructions, edit its `prompt.md` file.
- To change a mode's metadata (e.g., name, description), edit its `config.yaml` file.
- To add a new mode, create a new sub-directory in `/sources` with the required files and add its name to `manifest.yaml`.

</details>

<details>
<summary><b>Step 2: Build the Configuration File</b></summary>

Run the build script from the repository's root directory to generate the final `custom_modes.yaml`:
```bash
python roles_builder/build.py
```

</details>

<details>
<summary><b>Step 3: Link the Output File</b></summary>

The generated `custom_modes.yaml` is the file to be used by the AI agent. For Roo Code on Windows, place it at:
```
%APPDATA%\Code\User\globalStorage\rooveterinaryinc.roo-cline\settings\custom_modes.yaml
```

</details>

### 2. Custom Commands

Custom commands are managed by copying the templates directly.

To use the command templates, place the files from the `/commands` directory on Windows into:
```
%USERPROFILE%\.roo\commands\
```

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## 📄 License

This project is licensed under the **GNU Affero General Public License v3.0** — see the [LICENSE](LICENSE) file for details.

> **Note:** Prior commits without a license file were under exclusive copyright (All Rights Reserved).

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## 👤 Author

**Jwadow** — [@Jwadow](https://github.com/jwadow)

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