npx skills add https://github.com/github/awesome-copilot --skill comment-code-generate-a-tutorialHow Comment Code Generate A Tutorial fits into a Paperclip company.
Comment Code Generate A Tutorial drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.
Pre-configured AI company — 18 agents, 18 skills, one-time purchase.
SKILL.md26 linesExpandCollapse
---name: comment-code-generate-a-tutorialdescription: 'Transform this Python script into a polished, beginner-friendly project by refactoring the code, adding clear instructional comments, and generating a complete markdown tutorial.'--- Transform this Python script into a polished, beginner-friendly project by refactoring the code, adding clear instructional comments, and generating a complete markdown tutorial. 1. **Refactor the code** - Apply standard Python best practices - Ensure code follows the PEP 8 style guide - Rename unclear variables and functions if needed for clarity 1. **Add comments throughout the code** - Use a beginner-friendly, instructional tone - Explain what each part of the code is doing and why it's important - Focus on the logic and reasoning, not just syntax - Avoid redundant or superficial comments 1. **Generate a tutorial as a `README.md` file** Include the following sections: - **Project Overview:** What the script does and why it's useful - **Setup Instructions:** Prerequisites, dependencies, and how to run the script - **How It Works:** A breakdown of the code logic based on the comments - **Example Usage:** A code snippet showing how to use it - **Sample Output:** (Optional) Include if the script returns visible results - Use clear, readable Markdown formattingAdd Educational Comments
Takes any code file and transforms it into a teaching resource by adding educational comments that explain syntax, design choices, and language concepts. Automa
Agent Governance
When your AI agents start calling APIs, touching databases, or executing shell commands, you need guardrails before something goes sideways. This gives you comp
Agentic Eval
Implements self-critique loops where Claude generates output, evaluates it against your criteria, then refines based on its own feedback. Includes evaluator-opt