agent-md-refactor

🥈Silver

The agent-md-refactor skill automates Markdown documentation refactoring for developers. It simplifies complex refactoring tasks, saving time and effort. Connects to Claude for workflow automation.

1,449141,884installsUpdated Yesterday

Intermediate30min to implementautomation

Saves ~30 min per use

Quick InstallView Source

git clone https://github.com/softaworks/agent-toolkit.git

Works with:

Claude

Overview

About This Skill

The agent-md-refactor skill is designed to optimize the process of refactoring Markdown documentation. By automating repetitive tasks associated with Markdown formatting, this skill allows developers to focus on more critical aspects of their projects. It integrates seamlessly into existing workflows, making it a valuable addition to any AI agent toolkit. One of the key benefits of using agent-md-refactor is the significant time savings it offers. Developers often spend hours manually adjusting Markdown files to meet formatting standards or to improve readability. With this skill, those hours can be reduced to mere minutes, enabling teams to allocate resources more efficiently and enhance productivity. This skill is particularly beneficial for developers, product managers, and AI practitioners who regularly work with documentation. Whether you're maintaining project documentation, creating user manuals, or preparing reports, agent-md-refactor can streamline your workflow. For instance, if a developer needs to update a large set of Markdown files after a project change, this skill can automate the refactoring process, ensuring consistency and accuracy across all documents. Implementation of the agent-md-refactor skill is straightforward, making it accessible even for those who may not be deeply familiar with AI automation. It fits perfectly into AI-first workflows by enhancing the capabilities of AI agents, allowing them to handle documentation tasks that would otherwise consume valuable time. By incorporating this skill, teams can improve their overall efficiency and focus on delivering high-quality products.

How to Use

1. Copy your Markdown documentation into a text file or document 2. Identify specific aspects you want to improve (headings, lists, code blocks, etc.) 3. Paste the content into the prompt template, specifying your focus areas 4. Run the prompt in Claude or your preferred AI tool 5. Review the output and manually verify suggested changes Tip: For complex documents, process sections one at a time to maintain context

Use Cases

Automating the formatting of project documentation in Markdown

Refactoring Markdown files for better readability and consistency

Quickly updating multiple Markdown documents after project changes

Streamlining the creation of user manuals using Markdown

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/softaworks/agent-toolkit

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Refactor the following Markdown documentation to improve readability and structure. Focus on [SPECIFIC ASPECTS] like headings, lists, or code blocks. Here's the content: [PASTE_MARKDOWN_CONTENT]. Suggest changes to make it more maintainable and user-friendly. Provide the refactored version and a summary of key improvements.

Example Output

Original content had inconsistent heading levels and poorly formatted code blocks. Here's the refactored version with improved hierarchy and syntax highlighting:

```markdown
# API Reference

## Authentication

### Token Generation

```python
# Generate authentication token

def generate_token(api_key):
    # Implementation details
    return token
```

Key improvements:
1. Standardized heading levels (H1-H3)
2. Added clear section separation
3. Improved code block formatting with language specification
4. Added consistent spacing between elements
5. Simplified nested lists for better readability

The documentation is now more scannable and maintainable while preserving all original content.