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‎README.md‎

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# code-assistant-manager
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# Code Assistant Manager (CAM)
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<div align="center">
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[![PyPI Version](https://img.shields.io/pypi/v/code-assistant-manager?color=blue)](https://pypi.org/project/code-assistant-manager/)
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[![License](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
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[![Python Versions](https://img.shields.io/pypi/pyversions/code-assistant-manager.svg)](https://pypi.org/project/code-assistant-manager/)
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**Unified Python CLI for AI Coding Assistants**
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**One CLI to Rule Them All.**
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<br>
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Manage Claude, Codex, Gemini, Qwen, and more from a single, polished terminal interface.
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[Quick Start](#quick-start) • [Features](#core-features) • [Interactive Mode](#interactive-mode) • [Commands](#subcommands-reference) • [MCP Support](#model-context-protocol-mcp) • [Contributing](#contributing)
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Tired of juggling multiple AI coding assistants? **CAM** is a unified Python CLI to manage configurations, prompts, skills, and plugins for Claude, Codex, Gemini, Qwen, and more from a single, polished terminal interface.
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</div>
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---
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## Core Features
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* **Unified CLI:** One tool (`cam`) to manage multiple AI assistants.
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* **Interactive Menus:** Polished TUI for model selection and tool launching.
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* **Prompt Management:** Fetch, sync, and manage system prompts across different assistants.
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* **Skill Management:** Install and manage "skills" (tool definitions) for your AI agents.
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* **MCP Integration:** Full support for the Model Context Protocol (MCP) - manage servers and tools.
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* **Diagnostics:** Built-in `doctor` command to check environment health.
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* **Extensible:** Easy to add new models and providers via LiteLLM.
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## Quick Start
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### Installation
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```bash
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pip install code-assistant-manager
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```
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### Basic Usage
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Launch the interactive menu:
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```bash
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cam launch
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```
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## Interactive Mode
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The easiest way to use CAM is through the interactive launcher:
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```bash
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cam launch
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```
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This opens a centered menu where you can:
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* **Select Model:** Choose the active LLM model for your sessions.
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* **Launch Assistant:** Start specific assistants (Claude, Codex, etc.) with the selected configuration.
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* **Manage Settings:** Configure API keys and other preferences.
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## Why CAM?
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## Subcommands Reference
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In the era of AI-driven development, developers often use multiple powerful assistants like Claude, GitHub Copilot, and Gemini. However, this leads to a fragmented and inefficient workflow:
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- **Scattered Configurations:** Each tool has its own setup, API keys, and configuration files.
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- **Inconsistent Behavior:** System prompts and custom instructions diverge, leading to different AI behaviors across projects.
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- **Wasted Time:** Constantly switching between different CLIs and UIs is a drain on productivity.
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CAM offers a rich set of subcommands for advanced management.
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CAM solves this by providing a single, consistent interface to manage everything, turning a chaotic toolkit into a cohesive and powerful development partner.
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### Main Commands
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## Key Features
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| Command | Alias | Description |
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| :--- | :--- | :--- |
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| `cam launch` | `l` | Open the interactive menu or launch specific tools directly (e.g., `cam l claude`). |
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| `cam doctor` | `d` | Run diagnostic checks on your environment, API keys, and configuration. |
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| `cam version` | `v` | Display the current version of CAM. |
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| `cam upgrade` | `u` | Update underlying tools (like `claude-engineer`, `aider`, etc.) to their latest versions. |
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| `cam install` | `i` | Alias for `upgrade`. Installs or updates tools. |
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| `cam uninstall` | `un` | Uninstall CLI tools and optionally backup/remove their configuration files. |
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| `cam config` | `cf` | Manage configuration files. Use `cam config list` to see all config paths. |
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| `cam completion` | `c` | Generate shell completion scripts for Bash or Zsh. |
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- **Unified Management:** One tool (`cam`) to install, configure, and run all your AI assistants.
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- **Centralized Configuration:** Manage all API keys and settings from a single `.env` file.
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- **Interactive TUI:** A polished, interactive menu (`cam launch`) for easy navigation and operation.
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- **Extensible Framework:** Standardized architecture for managing:
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- **Agents:** Standalone assistant configurations.
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- **Prompts:** Reusable system prompts synced across assistants.
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- **Skills:** Custom tools and functionalities for your agents.
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- **Plugins:** Marketplace extensions for supported assistants.
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- **MCP Support:** First-class support for the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/), allowing assistants to connect to external data sources and tools.
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- **Diagnostics:** A built-in `doctor` command to validate your environment and connectivity.
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### Shell Completion
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## Feature Support Matrix
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Enable tab completion for `cam` commands in your shell.
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| Feature | Claude | Codex | Gemini | Qwen | LiteLLM |
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| :--- | :---: | :---: | :---: | :---: | :---: |
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| **Agent** Management | ✅ | ✅ | ✅ | ✅ | ✅ |
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| **Prompt** Syncing | ✅ | ✅ | ✅ | ✅ | ✅ |
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| **Skill** Installation | ✅ | ✅ | ✅ | ✅ | ✅ |
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| **Plugin** Support | ✅ | ❌ | ❌ | ❌ | ❌ |
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| **MCP** Integration | ✅ | ✅ | ✅ | ✅ | ✅ |
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**Bash:**
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```bash
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# Add to ~/.bashrc
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source <(cam completion bash)
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```
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**Zsh:**
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```zsh
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# Add to ~/.zshrc
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source <(cam completion zsh)
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```
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### Prompt Management (`cam prompt`)
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Manage and sync system prompts across all your AI assistants.
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## Installation
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```bash
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# List all available prompts
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cam prompt list
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# Fetch latest prompts from remote repositories
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cam prompt fetch
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# View details of a specific prompt
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cam prompt view <prompt_id>
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# Set a specific prompt as the default active prompt
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cam prompt set-default <prompt_id>
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# Sync the default prompt to all installed assistants
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cam prompt sync
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# Sync a specific prompt to a specific assistant
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cam prompt sync <prompt_id> --app gemini
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# Create a new prompt from a file
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cam prompt create my-new-prompt --file ./my_prompt.md
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# Import the current live prompt from an assistant
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cam prompt import-live --app claude --name "My Claude Prompt"
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```
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### Skill Management (`cam skill`)
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Equip your assistants with new capabilities (tools/skills).
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```bash
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# Discover available skills from configured repositories
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cam skill fetch
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# List all skills and their installation status
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cam skill list
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# View details of a skill
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cam skill view <skill_id>
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# Install a skill to a specific assistant (or 'all')
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cam skill install <skill_id> --app all
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# Uninstall a skill
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cam skill uninstall <skill_id>
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# Manage skill repositories
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cam skill repos # List repositories
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cam skill add-repo ... # Add a new GitHub repo
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pip install code-assistant-manager
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```
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### Model Context Protocol (`cam mcp`)
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Manage MCP servers to connect your AI assistants to external data and tools.
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## Quick Start
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```bash
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# List registered and installed MCP servers
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cam mcp server list
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1. **Set up API Keys:**
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Create a `.env` file in your home directory (`~`) or your project's root directory.
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# Search for available MCP servers
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cam mcp server search "postgres"
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```env
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# ~/.env or ./.env
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ANTHROPIC_API_KEY="sk-ant-..."
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OPENAI_API_KEY="sk-..."
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GEMINI_API_KEY="..."
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QWEN_API_KEY="..."
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```
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# Show details for a server
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cam mcp server show "postgres"
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2. **Check Your Setup:**
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Run the `doctor` command to verify that your API keys are correctly configured.
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# Install an MCP server
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cam mcp server add "postgres" --client all
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```bash
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cam doctor
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```
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# Remove an MCP server
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cam mcp server remove "postgres"
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```
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3. **Launch the Interactive Menu:**
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The easiest way to get started is with the interactive TUI.
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## Supported Assistants
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```bash
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cam launch
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```
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This menu allows you to select models, launch assistants, and manage settings without memorizing commands.
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CAM provides management and wrappers for:
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## Command Reference
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* **Claude** (Anthropic)
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* **Codex** (OpenAI / GitHub Copilot CLI)
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* **Gemini** (Google)
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* **Qwen** (Alibaba Cloud)
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* **LiteLLM** (Access to 100+ models via proxy)
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CAM provides a rich set of subcommands for power users.
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## Configuration
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| Command | Alias | Description |
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| :--- | :--- | :--- |
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| `cam launch` | `l` | Launch the interactive TUI or a specific assistant. |
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| `cam doctor` | `d` | Run diagnostic checks on your environment and API keys. |
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| `cam agent` | `a` | Manage and configure AI assistants (Agents). |
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| `cam prompt` | `p` | Manage and sync system prompts across all assistants. |
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| `cam skill` | `s` | Install and manage collections of tools (Skills). |
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| `cam plugin` | - | Manage marketplace extensions (Plugins). |
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| `cam mcp` | - | Manage Model Context Protocol (MCP) servers. |
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| `cam upgrade` | `u` | Upgrade CAM and all underlying assistant tools. |
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| `cam install` | `i` | Alias for `upgrade`. |
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| `cam uninstall` | `un` | Uninstall tools and manage their configuration files. |
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| `cam config` | `cf` | Manage CAM's internal configuration files. |
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| `cam completion`| `c` | Generate shell completion scripts. |
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| `cam version` | `v` | Display the current version of CAM. |
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CAM uses a combination of configuration files and environment variables.
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For detailed usage of each command, run `cam [COMMAND] --help`.
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* **Configuration Directory:** `~/.config/code-assistant-manager/` (Linux/Mac)
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* **Environment Variables:** Create a `.env` file in your project root or home directory.
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## How It Works: Architecture Overview
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Example `.env`:
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```env
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OPENAI_API_KEY=sk-...
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ANTHROPIC_API_KEY=sk-ant-...
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GEMINI_API_KEY=...
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```
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CAM is built on a modular and extensible architecture.
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- **Entry Point:** The CLI is powered by **Typer**, with the main app defined in `code_assistant_manager/cli/app.py`.
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- **Manager/Handler Pattern:** A key design pattern is the use of a `Manager` class for each core concept (e.g., `AgentManager`, `SkillManager`). These managers handle the generic logic of fetching, caching, and managing extensions.
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- **App-Specific Logic:** For each supported AI assistant (like Claude), there is a corresponding `Handler` class (e.g., `ClaudeAgentHandler`) that contains the specific logic for installing an agent or skill in the correct directory for that application. This decouples the core logic from the specifics of each tool.
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- **Extensible by Design:** This architecture makes it straightforward to add support for new assistants or new types of extensions in the future.
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## Contributing
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### Development Setup
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Contributions are welcome! Please see our [Developer Guide](docs/DEVELOPER_GUIDE.md) and [Contributing Guidelines](docs/CONTRIBUTING.md) to get started.
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1. Clone the repository:
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```bash
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git clone https://github.com/Chat2AnyLLM/code-assistant-manager.git
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cd code-assistant-manager
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```
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### Development Setup
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2. Install dependencies:
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1. Clone the repository.
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2. Install in editable mode with development dependencies:
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```bash
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pip install -e ".[dev]"
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```
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3. Run tests:
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```bash
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pytest tests/
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pytest
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```
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### Repository Structure
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* `code_assistant_manager/`: Main package source.
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* `cli.py`: Entry point.
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* `mcp/`: MCP subsystem.
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* `prompts.py`: Prompt logic.
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* `skills.py`: Skill logic.
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* `tests/`: Comprehensive test suite.
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See [docs/](docs/) for more detailed developer guides.
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## License
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This project is licensed under the MIT License.

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