using-superpowers

Enforce proactive skill invocation before answering or acting.

4|2|Updated Jan 25, 2026
One-click install
npx skills add https://github.com/lyfe2025/lyfes-coding-skills --skill using-superpowers-lyfe2025
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: using-superpowers
Source: https://github.com/lyfe2025/lyfes-coding-skills/tree/main/skills/superpowers/using-superpowers
Command: npx skills add https://github.com/lyfe2025/lyfes-coding-skills --skill using-superpowers-lyfe2025

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enforces proactive skill invocation at the start of every interaction, ensuring the correct capabilities are considered before responding.

Core Features & Use Cases

  • Mandatory early skill invocation: Whenever a task could be addressed by a skill, you must invoke it before answering.
  • Declarative communication: It announces the selected skill and purpose to maintain traceability, safety, and alignment.
  • Workflow integration: It defines a repeatable flow (invoke → announce → checklists → execute) that coordinates AI agents and humans on complex tasks.

Quick Start

Use the Skill tool at the start of any task that might require a skill, then follow the announced workflow to proceed.

Frequently Asked Questions about using-superpowers

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce proactive AI skill invocation at the start of a development workflow?

Proactive AI skill invocation is enforced by requiring the assistant to invoke applicable skills before answering or acting on a task. This ensures correct capabilities are considered early and maintains alignment in the development workflow.

What is a checklist-driven workflow for coordinating AI agents on complex tasks?

A checklist-driven workflow coordinates AI agents and humans by following deterministic steps: invoke a skill, announce the selected skill and purpose, execute checklists, and perform the task. This repeatable flow ensures traceable and safe task execution.

How do I maintain traceability when integrating AI workflows into software engineering tasks?

Traceability in AI workflows is maintained through declarative communication, where the assistant announces the selected skill and its purpose before execution. This practice ensures every action is aligned and traceable back to a specific capability.

Do I need to manually select a skill before starting an AI-assisted development task?

Manual selection is not needed. Whenever a task could be addressed by a skill, the system proactively identifies and invokes the appropriate skill automatically at the start of the interaction, guiding the assistant to act before answering.

What are the limitations of using prompt discipline for deterministic AI task execution?

Prompt discipline for deterministic AI execution relies on the assistant consistently following the invoke-announce-checklist-execute flow. Limitations arise if the task lacks an addressable skill or if the AI bypasses the mandatory early invocation step, breaking the deterministic workflow.