Execute Defined Workflows and Actions
A skill that teaches AI assistants how to discover, understand, and use other skills in their environment through structured capability exploration.
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Why it matters
This asset ensures that AI agents rigorously follow predefined workflows and execute tasks according to established rules and best practices. It acts as a meta-skill, guiding the AI's decision-making process to prioritize and correctly apply other skills.
Outcomes
What it gets done
Invoke relevant skills before responding
Follow skill instructions precisely
Determine skill applicability based on task context
Prioritize skills based on type (process vs. implementation)
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-using-superpowers | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
Reports
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Overview
Using Skills
This skill teaches AI assistants how to discover and use other skills available in their environment. It provides a structured method for assistants to explore their capabilities, understand what tools they have access to, and invoke them appropriately during interactions. Use this when building AI assistants that need to dynamically discover their own capabilities, especially in environments where skills are frequently added or modified. It's ideal for creating self-aware assistants that can explain and utilize their available functionality.
What it does
This skill enables AI assistants to discover and utilize other available skills in their environment. It provides a structured approach for assistants to explore their own capabilities, understand what tools and skills are at their disposal, and invoke them appropriately during conversations.
When to use - and when NOT to
Use this skill when you need an AI assistant to dynamically discover what it can do, especially in environments where skills are added or changed frequently. It's valuable when building assistants that need to be self-aware of their capabilities and can explain their own functionality to users.
Do NOT use this as a replacement for direct skill invocation when you already know exactly which skill you need. Do NOT rely on it in scenarios where skill discovery overhead would slow down time-critical operations.
Inputs and outputs
Users provide queries or requests that require the assistant to first understand what capabilities it has available. The assistant receives structured information about available skills, their purposes, and how to invoke them. The output is the assistant's ability to correctly identify, select, and use the appropriate skill from its available set to fulfill the user's request.
Who it's for
This skill is designed for developers building AI assistants that operate in dynamic environments where the set of available capabilities may change. It's particularly useful for platform builders creating extensible AI systems where skills can be added modularly. It differs from static skill configurations by enabling runtime capability discovery rather than requiring hardcoded knowledge of available tools.
Source README
This is not negotiable. This is not optional. You cannot rationalize your way out of this.
FAQ
Common questions
Discussion
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