aeo

This Skill addresses the challenges faced by website developers and operators when conducting SEO audits, performance diagnostics, and compliance checks—such as the need to switch between multiple tools, manually analyze reports, and the difficulty of automating these tasks within CI/CD pipelines. In practice, developers often need to assess the SEO impact of new features, compare differences between production and preview environments, or generate compliant AI search files (e.g., llms.txt) for statically generated sites—tasks that are tedious and error-prone.

Usage is straightforward: simply run npx @ainyc/aeo-audit@1 "<url>" [flags] --format json via the command line, specifying different modes (e.g., audit, fix, schema, llms, monitor). You can then use natural language instructions to obtain detailed JSON-formatted reports, which include overall scores, issue summaries, fix suggestions, and even automatically apply code fixes, generate or optimize llms.txt files, and perform regression comparisons.

It is well-suited for frontend/backend developers, DevOps engineers, and SEO specialists who require continuous monitoring and optimization of website quality—particularly teams or individuals using static site generators, managing multiple preview branches (e.g., Staging), or needing to ensure website content is friendly to AI search engines. For product managers and data analysts, it also provides objective data to evaluate website health.

It is recommended to integrate this tool into automated audits before code merges or within daily build pipelines to identify issues early. Note that it primarily focuses on technical SEO and basic performance metrics; for in-depth content strategy analysis or complex user experience optimization, other specialized tools may be needed. Additionally, when using local or private preview URLs, security parameters such as --allow-local must be explicitly added.