orchestration:executing-workflows

What problem does it solve?

Executing complex AI workflows can be an opaque process, making it difficult to track progress, intervene in errors, or understand the flow. This Skill provides transparent execution with real-time visualization and interactive steering, giving you full control and clarity over your automated tasks.

Core Features & Use Cases

• Real-time Visualization & Progress Tracking: Displays an ASCII art execution graph and updates progress as agents run, offering immediate insight into your workflow's status.
• Interactive Steering & Error Recovery: Allows you to pause at checkpoints, make critical decisions, retry failed steps, or modify instructions on-the-fly during execution, ensuring flexible and resilient automation.
• Comprehensive Syntax Support: Fully supports sequential, parallel, and conditional execution, robust variable passing, and dynamic temporary agents, enabling you to build highly sophisticated workflows.
• Mandatory Cleanup: Ensures all temporary files (scripts, agents, state) are automatically and thoroughly cleaned up after every execution, keeping your workspace tidy and efficient.
• Use Case: You're running a multi-stage deployment workflow. At a "staging-approval" checkpoint, you can review the staging environment, and if issues are found, you can choose to retry a previous step or abort the deployment before it reaches production, all from within the execution flow.

Quick Start

Run this workflow: Explore:"Analyze codebase":analysis -> implement:"Add feature based on {analysis}" -> general-purpose:"Run tests"