@0xkobold/pi-orchestration

This Skill addresses the complex workflow management challenges in multi-agent collaborative orchestration. In practical development, when multiple AI agents need to work together sequentially, in parallel, or in a forked manner to complete tasks, manually managing communication, context passing, and depth limits is often tedious and error-prone. pi-orchestration provides a standardized set of orchestration patterns, allowing developers to define multi-agent workflows as easily as writing regular code, without worrying about underlying scheduling details.

Usage is straightforward: simply import the orchestrate function and specify the execution mode (agent for single-step, chain for sequential, parallel for parallel) via the options parameter. You can then describe tasks using natural language instructions, such as defining a series of agent types (e.g., scout, worker, reviewer) and their task descriptions. The system automatically selects the optimal model for each agent based on depth limits and the model registry, and supports work tree isolation to ensure subtasks do not interfere with each other.

It is well-suited for teams or individuals requiring multi-step collaborative AI coding. Developers already using pi-coding-agent as their foundational coding agent can seamlessly integrate this orchestration library to quickly build end-to-end pipelines—from code analysis and solution design to implementation and review. Project managers can also use it to assign team tasks and track the execution status and outputs of each subtask.

It is recommended to adopt this tool uniformly for orchestrating multiple AI agents in complex projects, such as multi-module refactoring or cross-functional feature development. Note that it primarily relies on pi-coding-agent's model registry and context; it cannot run independently outside the pi-coding-agent environment. Additionally, when using parallel execution, it is advisable to set reasonable concurrency limits to avoid overloading.