ScreamingFrogR
🥈SilverScreamingFrogR automates SEO tasks by processing exports from the Screaming Frog SEO Spider tool. Designed for SEO professionals and analysts working with crawl data.
920Updated 4mo ago
Intermediate30min to implementmarketing
Saves ~90 min per use
Quick InstallView Source
git clone https://github.com/remibacha/ScreamingFrogR.gitWorks with:
Claude
Overview
About This Skill
ScreamingFrogR is an R-based project that automates SEO tasks by working with data exported from Screaming Frog SEO Spider. It targets SEO professionals and data analysts who regularly handle large crawl datasets and want to streamline repetitive analysis workflows. By leveraging R's data processing capabilities, the skill enables users to work programmatically with Screaming Frog export files rather than manually reviewing them. The project is maintained by Rémi Bacha and is available as an open-source repository on GitHub.
How to Use
["Export your Screaming Frog crawl data (CSV or Excel format) from the tool by going to 'Export' > 'All' > 'All Inlinks' or 'All Pages'. Save the file to a known location on your device.","Upload or attach the exported file to your AI tool (e.g., Claude, ChatGPT, or a custom R/Python script using the ScreamingFrogR package). Ensure the file is in a supported format (CSV, Excel, or JSON).","Specify the issues to focus on using the prompt template. For example, replace [SPECIFIC_ISSUES] with 'broken links, duplicate content, and missing meta descriptions' and [TARGET_AREAS] with 'internal linking structure and page speed'.","Review the AI-generated action plan, prioritizing issues based on impact and effort. Cross-reference the recommendations with your CMS or development team's capabilities to ensure feasibility.","Implement the fixes in your CMS or development environment. Use the AI's suggestions for redirects, meta descriptions, or image optimization tools. Re-crawl the site after changes to validate improvements."]
Use Cases
Automate analysis of Screaming Frog crawl export CSV files
Process large-scale site audit data programmatically using R
Streamline repetitive SEO reporting tasks from crawl exports
Batch-process technical SEO data for multiple site crawls
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/remibacha/ScreamingFrogRRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Process the Screaming Frog SEO Spider export file [FILE_PATH] to identify [SPECIFIC_ISSUES] such as broken links, duplicate content, missing meta descriptions, or slow-loading pages. Generate a prioritized action plan with recommendations for fixing each issue, including estimated effort (low/medium/high) and impact (low/medium/high). Focus on [TARGET_AREAS] like internal linking structure or page speed optimizations.
Example Output
After analyzing the Screaming Frog export for 'AcmeCorp.com' (crawl completed on 2023-11-15), the AI identified 47 critical issues requiring immediate attention. The most urgent problems include: 1) 12 broken internal links (404 errors) on product pages, primarily affecting the '/electronics' category, with an estimated 15-minute fix per link via URL redirects; 2) 8 pages missing meta descriptions, including the homepage and top 5 service pages, which could improve CTR by 8-12% with a 5-minute fix per page; 3) 5 slow-loading pages (load time >3s) in the blog section, where compressing images could reduce load time by 40%. The action plan prioritizes fixing broken links first (high impact, low effort), followed by meta descriptions (medium impact, low effort), and image optimization (medium impact, medium effort). For the broken links, the AI suggests creating a redirect map using .htaccess rules to consolidate similar URLs and preserve link equity. The meta descriptions should include primary keywords from the page content and a compelling call-to-action. For image optimization, the AI recommends using TinyPNG or Squoosh to compress files without losing quality. The total estimated time to resolve all issues is 4-6 hours, with potential SEO improvements including a 15-20% increase in organic traffic within 3 months if all recommendations are implemented.
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