SEO-Automation-Project

🥈Silver

This Python-based SEO automation toolkit includes five powerful scripts to streamline SEO tasks: redirect map automation, bulk meta descriptions generation, keyword analysis with N-grams, keyword clustering, and matching keywords to predefined topics. Save time and improve your SEO strategy efficiently!

520Updated 4mo ago

Intermediate30min to implementmarketing

Saves ~300 min per use

Quick InstallView Source

git clone https://github.com/ridetored/SEO-Automation-Project.git

Works with:

Claude

Overview

About This Skill

SEO Automation Project is a Python-based toolkit that eliminates repetitive SEO work through five specialized scripts. It automatically generates redirect maps by matching old and new URLs, creates bulk meta descriptions using LSA summarization, analyzes keywords with unigrams/bigrams/trigrams, clusters keywords into topic groups using TF-IDF and Affinity Propagation, and matches keywords to predefined topics via Spacy NLP. The toolkit handles large datasets efficiently by leveraging multi-core processors, making it ideal for SEO professionals and content teams managing hundreds or thousands of pages. Installation requires Python 3.7+ and dependencies from requirements.txt, with all tasks executable through a unified command-line interface.

How to Use

Clone the repository and install dependencies with pip install -r requirements.txt. Run tasks via python main.py --task [task_name], where task names are: redirect, meta, ngrams, clusters, or match. Prepare input files in the data/ directory (source_urls.txt, keywords.txt, etc.) and retrieve results from the results/ directory.

Use Cases

Generating redirect maps when migrating website URLs

Bulk creating meta descriptions for large content libraries

Identifying keyword patterns with N-gram analysis

Organizing keywords into topic clusters for content strategy

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/ridetored/SEO-Automation-Project

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

I need to automate my SEO tasks using Python. Create a project plan for implementing the following scripts: 1) Redirect map automation, 2) Bulk meta descriptions generation, 3) Keyword analysis with N-grams, 4) Keyword clustering, and 5) Matching keywords to predefined topics. My [COMPANY] operates in the [INDUSTRY] sector and I have [DATA] to work with. Provide a step-by-step implementation guide.

Example Output

# SEO Automation Project Plan

## Project Overview

This project aims to streamline SEO tasks for [COMPANY], operating in the [INDUSTRY] sector, using Python-based automation scripts. The project will focus on five key areas:

- Redirect map automation
- Bulk meta descriptions generation
- Keyword analysis with N-grams
- Keyword clustering
- Matching keywords to predefined topics

## Implementation Steps

1. **Redirect Map Automation**
   - Gather existing URL mappings
   - Implement Python script to automate redirect mapping
   - Test and validate redirects

2. **Bulk Meta Descriptions Generation**
   - Analyze current meta descriptions
   - Develop script to generate optimized meta descriptions
   - Integrate with CMS

3. **Keyword Analysis with N-grams**
   - Collect keyword data
   - Implement N-gram analysis script
   - Identify high-value keywords

4. **Keyword Clustering**
   - Group related keywords
   - Implement clustering algorithm
   - Validate keyword clusters

5. **Matching Keywords to Topics**
   - Define predefined topics
   - Develop script to match keywords to topics
   - Review and refine topic assignments

## Timeline

- Week 1-2: Redirect Map Automation and Bulk Meta Descriptions
- Week 3-4: Keyword Analysis and Clustering
- Week 5: Keyword-Topic Matching and Final Review

## Expected Outcomes

- Improved SEO efficiency
- Enhanced keyword strategy
- Streamlined SEO workflows

## Resources Needed

- Python development environment
- Access to SEO tools and data
- Collaboration with marketing team