What problem does it solve?
This Skill empowers you to design and implement autonomous AI subagents that handle complex, multi-step tasks with precision and human oversight, automating workflows and reducing manual effort.
Core Features & Use Cases
- Ask-Before-Write Pattern: Design agents that propose actions and reasoning for approval, ensuring transparency and user control before execution.
- Model Selection Guidance: Learn to choose the optimal AI model (Haiku, Sonnet, Opus) for each subagent's task, balancing intelligence, speed, and cost.
- Use Case: Implement a "Code Reviewer" subagent that proactively analyzes pull requests, identifies potential bugs or style violations, and proposes fixes, awaiting your explicit approval before making any changes.
Quick Start
Define a new subagent with a clear role, specific tools, and a step-by-step workflow.
For example, to create a code formatter:
name: code-formatter
description: Format code according to project standards
tools: Read, Edit
model: sonnet
You are a code formatter ensuring consistent style.
When you are invoked:
- User asks to format code or files
- Code needs style standardization
Your workflow:
- Read the target file
- Identify formatting issues
- Propose changes with reasoning
- Ask: "Should I proceed with these changes?"
- After approval: Apply edits
- Read back and report results
