mcgravity

mcgravity is an innovative automation skill designed to orchestrate AI coding tools such as Claude Code, Codex, and Gemini in a structured plan-execute-review loop. This fast terminal user interface (TUI) breaks down complex work into atomic tasks, allowing for easier verification and course correction. By facilitating a clear workflow, mcgravity enhances the efficiency of coding processes, making it a valuable asset for developers and product managers alike. The key benefits of mcgravity include improved task management and streamlined collaboration among AI agents. By segmenting work into manageable components, users can quickly assess progress and make necessary adjustments, ultimately saving time in the development cycle. Although the exact time savings are currently unknown, the skill's design promotes a more efficient workflow, which can lead to significant reductions in project timelines when implemented effectively. This skill is particularly suited for developers, product managers, and AI practitioners who are looking to enhance their coding workflows. It is ideal for teams that rely heavily on AI automation and need to ensure that their coding tasks are executed with precision. With its intermediate implementation difficulty, mcgravity can be set up in just 30 minutes, making it accessible for those familiar with AI tools and coding environments. Practical use cases for mcgravity include automating repetitive coding tasks, improving code quality through iterative reviews, and facilitating collaboration between multiple AI agents. For instance, a development team could use mcgravity to coordinate a project involving multiple AI tools, allowing them to efficiently manage tasks such as code generation, testing, and debugging. As organizations increasingly adopt AI-first workflows, mcgravity stands out as a crucial skill that enhances productivity and streamlines the development process.

[{"step":"Install McGravity and configure your preferred AI coding tool (Claude Code, Codex, or Gemini) with API keys.","action":"Run `pip install mcgravity` and set environment variables for your AI tool's API key.","tip":"Use the tool's official CLI to test API connectivity before starting McGravity sessions."},{"step":"Define your task and verification criteria in the McGravity configuration file.","action":"Create a `mcgravity.yaml` file with fields like `issue_description`, `project_name`, and `verification_criteria`.","tip":"Be specific with verification criteria - include test commands, log checks, or manual review steps."},{"step":"Start the McGravity session and monitor atomic task execution.","action":"Run `mcgravity run --config mcgravity.yaml` and watch the TUI interface.","tip":"Use the pause/resume feature to inspect intermediate results if a task fails verification."},{"step":"Review the generated log file and address any remaining issues.","action":"Check the log in `/logs/` and manually fix any steps marked as failed.","tip":"For complex issues, break the task into smaller sub-tasks in your McGravity config."},{"step":"Integrate McGravity into your CI/CD pipeline for automated issue resolution.","action":"Set up a GitHub Actions workflow that triggers McGravity when issues are labeled 'autofix'.","tip":"Start with non-critical issues to validate the workflow before production use."}]