What problem does it solve?
This skill enables reliable orchestration of AI agents into pipelines with clear data handoffs, allowing complex tasks to be decomposed into modular, repeatable workflows.
Core Features & Use Cases
- Sequential pipelines: chain agents in order to transform data through multiple steps.
- Branching pipelines: route tasks based on intermediate results.
- Parallel-then-merge: run independent stages in parallel and merge outputs.
- Built-in presets and custom syntax for designing workflows.
- Data passing protocol and state management to persist execution context across stages.
- Robust error handling and retry strategies.
- Use cases include code review, feature implementation, research, and multi-stage automation across software projects.
Quick Start
Start by describing your desired workflow, for example: explore -> architect -> executor, or use a command like /pipeline review "optimize authentication" to automatically create and run a pipeline.