CodeKanban centralizes management of terminals and AI coding agents like Claude Code and Codex. Operations teams use it to streamline workflows, track progress, and improve collaboration across coding projects. It integrates with existing development tools and workflows.
git clone https://github.com/fy0/CodeKanban.gitCodeKanban is an innovative automation skill designed to streamline the management of multiple terminals and AI coding agents from a single, unified interface. This skill simplifies the workflow for developers and AI practitioners by consolidating various coding environments, allowing users to focus on coding without the hassle of switching between different terminals. With an implementation time of just 30 minutes, CodeKanban offers a straightforward setup process that enables users to quickly enhance their productivity. One of the key benefits of using CodeKanban is the potential for significant time savings, as it reduces the friction associated with managing multiple coding environments. By centralizing terminal management, users can easily access their AI agents and coding tools without the need for constant navigation, thus allowing for a more efficient workflow. While the exact time savings are currently unknown, the reduction in context-switching alone can lead to improved focus and faster project completion. This skill is particularly beneficial for developers, product managers, and AI practitioners who are involved in complex projects requiring collaboration across various coding environments. By utilizing CodeKanban, teams can enhance their workflow automation, ensuring that all coding agents are effectively managed and monitored. Practical use cases include managing deployment processes, coordinating team coding efforts, and integrating with existing CI/CD pipelines, all of which can be executed seamlessly through the CodeKanban interface. With an intermediate level of complexity, CodeKanban is suitable for users who have some experience with automation tools and coding environments. It fits perfectly into AI-first workflows by enabling teams to leverage AI agents more effectively, ensuring that they can maximize their potential while minimizing the time spent on manual management tasks. As organizations increasingly adopt AI automation, skills like CodeKanban will play a crucial role in enhancing productivity and driving innovation.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/fy0/CodeKanbanCopy 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.
Create a CodeKanban dashboard for [COMPANY] that integrates with [TERMINAL_1], [TERMINAL_2], and [TERMINAL_3]. Include AI coding agents [AGENT_1], [AGENT_2], and [AGENT_3]. The dashboard should display real-time status updates, task assignments, and progress tracking. Highlight any errors or bottlenecks.
# CodeKanban Dashboard for TechInnovate Solutions ## Terminal Status - **Terminal 1 (Dev-Env-01)**: Active, processing migration script - **Terminal 2 (QA-Env-02)**: Idle, last task completed 2 hours ago - **Terminal 3 (Prod-Env-03)**: Active, deploying new features ## AI Agent Assignments - **Agent 1 (CodeOptimizer)**: Refactoring legacy code in branch `feature/optimize` - **Agent 2 (BugHunter)**: Scanning for vulnerabilities in `api/services` - **Agent 3 (DocuGen)**: Generating API documentation for `v2.1.0` ## Alerts - **High Priority**: Terminal 3 deployment failed at 3:45 PM (Error: Dependency conflict) - **Medium Priority**: Agent 2 found 5 low-risk vulnerabilities ## Progress Tracking - **Current Sprint**: 65% complete - **Upcoming Tasks**: 12 tasks in backlog **Next Steps**: Resolve deployment error in Terminal 3, review Agent 2 findings, and assign new tasks to idle terminals.
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