superset

Superset is an innovative automation skill designed for orchestrating multiple agents, including Claude Code and OpenCode, directly from your terminal. This skill allows developers and AI practitioners to run a team of CLI agents on their machines, enabling seamless collaboration and task execution. By leveraging Superset, users can manage various coding agents in parallel, significantly enhancing productivity and efficiency in development workflows. One of the key benefits of using Superset is its ability to isolate different projects within separate git worktrees, effectively avoiding conflicts that can arise during development. This feature is particularly valuable for teams working on multiple projects simultaneously. Additionally, Superset provides a centralized interface for monitoring the status of various agents, allowing users to receive notifications and updates in real-time. This streamlined approach not only saves time but also simplifies the management of complex development environments. Superset is ideal for developers, product managers, and AI practitioners who are looking to optimize their workflow automation. With its intermediate implementation difficulty, users can set up Superset in approximately 30 minutes. The skill is particularly beneficial for those who need to quickly review and edit code changes, thanks to its built-in diff viewer. Moreover, it allows for the establishment of automated environments for new projects using workspace presets, making it easier to onboard new team members or initiate new tasks. Incorporating Superset into your AI-first workflows can significantly enhance your team's efficiency and collaboration. As organizations increasingly adopt AI automation, having a robust tool like Superset can help streamline processes and improve overall productivity. With its practical use cases, such as running multiple coding agents in parallel and monitoring their performance from a single interface, Superset stands out as a valuable asset for anyone looking to leverage AI agent skills effectively.

["Install Superset via pip: `pip install superset-terminal` and verify installation with `superset --version`. Ensure your system has Docker installed if using containerized agents.","Configure your AI agents in the Superset config file (superset.json) by specifying their CLI commands, resource limits (CPU/memory), and timeout settings. Example: `{ \"agents\": [ { \"name\": \"frontend-refactor\", \"command\": \"claude-code --workspace /projects/myapp/frontend\", \"max_memory\": \"4GB\" }, { \"name\": \"backend-refactor\", \"command\": \"opencode --project /projects/myapp/backend\", \"max_cpu\": \"2\" } ] }`","Define your task scope in a YAML/JSON file (e.g., `task.yaml`) with clear objectives, input files, and success criteria. Example: `objective: Refactor authentication module with zero breaking changes. inputs: [\"src/auth/\", \"tests/auth_test.py\"]. success_criteria: [\"All tests pass\", \"Latency < 100ms\", \"No security regressions\"]`.","Launch the orchestration with `superset run --task task.yaml --agents frontend-refactor,backend-refactor`. Monitor progress in real-time using `superset monitor --task task.yaml` and adjust agent priorities or resources as needed via the Superset dashboard.","Review the consolidated output in `superset-output/` directory. Use the diff report to validate changes against your success criteria. For conflicts, Superset provides automated resolution suggestions or manual override options. Iterate by updating the task.yaml and re-running Superset as needed."]