How It Works
The Data Science suite of MAGIC Agent Skills transforms any AI coding assistant into a data agent — an assistant specialized in data engineering, data processing, and data science workflows. It does this through self-contained knowledge packages called skills.
Each skill teaches your AI coding assistant how to think about data tasks through three layers:
The 3-Layer Architecture
Domain Knowledge
What the agent needs to understand about the task domain. Includes natural-language triggers (when to activate), rules, constraints, and anti-patterns to avoid.
Code Patterns
Seed patterns, templates, and reference implementations the agent studies and adapts to your specific task. These are not executed directly — the agent reads them and writes its own custom code tailored to your data.
Procedures
Step-by-step workflows the agent follows. Reference scripts in scripts/ demonstrate approaches — the agent studies them for patterns, then writes code adapted to the specific task at hand.
How the Agent Uses Skills
When your AI coding assistant receives a data task, it follows this process:
- Reads SKILL.md — gets domain knowledge, code patterns, and procedures
- Reads references — detailed reference docs loaded on demand for deeper context
- Reads scripts — studies reference implementations to understand proven approaches
- Writes its own code — adapts patterns to your specific data, format, and requirements
- Verifies quality — uses the constraints and rules from the skill to validate its work
Skills provide knowledge and patterns. The agent decides how to act — it may follow the reference scripts closely, adapt them significantly, or write entirely custom code depending on the situation.
Agent Autonomy
Skills guide — they don't force. Your AI assistant reads the SKILL.md, understands the domain, and makes intelligent decisions about how to apply the patterns to your specific situation. This means:
- The agent adapts code to your data format and structure
- It skips unnecessary steps when they don't apply
- It combines multiple skills when your task spans domains
- It explains its reasoning as it works
The Workflow
Every data task follows a natural pipeline orchestrated by the magic-data-lifecycle skill:
Discover → Plan → Execute → Validate → Deliver
Each phase routes to the right skill automatically. Not every step is needed for every task — the agent adapts the sequence to what your data actually needs.
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