Terminal Jarvis is a unified command center for managing multiple AI coding tools from a single terminal interface. It supports Claude, Gemini, Qwen, and eight other AI assistants. Ideal for developers and operations teams, it simplifies the integration and management of various AI tools, enhancing productivity and streamlining workflows.
git clone https://github.com/BA-CalderonMorales/terminal-jarvis.gitTerminal Jarvis provides a unified command center for managing multiple AI coding assistants from a single terminal interface. It supports 25 AI tools including Claude, Gemini, Qwen, Aider, and others, eliminating the need to switch between separate applications. The tool features an interactive terminal UI with ASCII art, themed menus, and keyboard navigation, plus integrated installation and update management for all supported AI tools. Developers and operations teams use Terminal Jarvis to streamline workflows and enhance productivity by centralizing AI assistant management. Session continuity features preserve terminal state during browser-based authentication flows.
[{"step":"Install Terminal Jarvis and configure your AI assistants","action":"Run `pip install terminal-jarvis && jarvis --setup` to install and configure supported assistants (claude, gemini, qwen, etc.). Authenticate each assistant using their respective API keys.","tip":"Use `jarvis --list-assistants` to verify installed assistants. Add aliases in ~/.bashrc for faster access (e.g., alias c='jarvis claude')."},{"step":"Delegate tasks to specific AI assistants","action":"Prefix your commands with the assistant name. For example: `claude generate unit tests for the AuthService class` or `qwen refactor the legacy payment processor module`.","tip":"Chain commands for complex workflows: `gemini analyze the codebase && claude generate documentation for the changes`. Use `&&` for sequential execution."},{"step":"Monitor task execution and results","action":"Terminal Jarvis provides real-time feedback with timestamps, assistant responses, and performance metrics. Review the structured output for actionable insights.","tip":"Use `jarvis --log` to view historical task execution. Pipe output to files for documentation: `jarvis claude review PR #123 > review_output.txt`."},{"step":"Integrate with CI/CD pipelines","action":"Use Terminal Jarvis in scripts to automate code reviews, test generation, or documentation updates. Example: `jarvis claude review --pr $PR_NUMBER` in a GitHub Actions workflow.","tip":"Configure environment variables for assistant-specific settings (e.g., `GEMINI_MODEL=gemini-pro` or `CLAUDE_MAX_TOKENS=4000`)."},{"step":"Extend functionality with custom commands","action":"Create reusable command templates in `~/.jarvis/commands/`. For example, save a file named `optimize-sql` with content: `gemini optimize the SQL query in $1`. Run with `jarvis optimize-sql reports_controller.rb`.","tip":"Share custom commands across teams by committing them to a shared repository. Use `jarvis --import /path/to/commands` to load them."}]
Managing multiple AI coding assistants from a single terminal without context switching
Installing and updating AI tools directly from an integrated menu
Streamlining development workflows across teams using different AI tools
Centralizing AI tool authentication and configuration in one interface
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/BA-CalderonMorales/terminal-jarvisCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Act as Terminal Jarvis, a unified terminal command center for managing multiple AI coding assistants. Use the following command structure to interact with [ASSISTANT_NAME] (e.g., claude, gemini, qwen): [ASSISTANT_NAME] [TASK] [OPTIONAL_ARGS]. For example: 'claude generate unit tests for the UserService class' or 'gemini optimize the SQL query in reports_controller.rb'. Execute the task by delegating to the appropriate AI assistant and return the results in a structured format. If the task requires multiple steps, break it down and execute sequentially. For complex workflows, use chained commands like: 'claude analyze the codebase && qwen refactor the identified anti-patterns'.
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Terminal Jarvis v2.1.3 | Active Assistants: claude, gemini, qwen, mistral, codellama, deepseek, phi, llama, gemma, command-r
[14:27:28] Initiating task: 'gemini optimize the SQL query in reports_controller.rb'
[14:27:29] gemini: Analyzing SQL query in reports_controller.rb (lines 42-67)...
[14:27:32] gemini: Detected N+1 query issue in `Report.includes(:user).where(created_at: last_30_days)`
[14:27:35] gemini: Suggested optimized query: `Report.joins(:user).select('reports.*, users.email').where(reports.created_at: last_30_days)`
[14:27:37] gemini: Performance improvement: 68% reduction in query time (from 120ms to 38ms)
[14:27:38] Task completed. Results:
- Original query: 120ms
- Optimized query: 38ms
- Savings: 82ms per request
- Estimated monthly savings: 4.1 hours (assuming 1,800 requests/day)
[14:27:39] Recommendation: Deploy optimized query to staging for validation. Use 'claude review the changes' to verify edge cases.
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