name	aeo-generate
description	Use when creating llms.txt, JSON-LD structured data, or robots.txt AI crawler configuration for a website or project build output

AEO Generate — AI Infrastructure Files

Generate AI infrastructure files from existing website content to make it discoverable by AI search engines.

File	Purpose
`llms.txt`	Machine-readable site summary for LLMs (llmstxt.org standard)
`llms-full.txt`	Full content version for deep AI consumption
`_aeo/generated-schemas.json`	JSON-LD schemas (Article, FAQPage, BreadcrumbList)
robots.txt suggestions	AI crawler allow/deny rules (printed, not auto-applied)

Identify build output. Ask the user for the directory containing their built site (e.g., dist/, out/, build/). Check for common framework patterns:
- Next.js: .next/ or out/
- Vite/Astro: dist/
- Hugo/Jekyll: public/
Preview first. Run:
```
npx aeoptimize generate <dir> --dry-run
```
Show the user what will be generated and explain each file's purpose.
Confirm and generate. On approval:
```
npx aeoptimize generate <dir>
```
Review generated files. Read each generated file and suggest manual refinements:
- llms.txt: Verify site name, description, and page listing are accurate
- JSON-LD: Check that generated schemas match the actual content
- robots.txt: Explain each AI crawler and let user decide allow/deny
Integration guidance. Explain how to deploy:
- Place llms.txt at site root (alongside robots.txt)
- Add <link rel="llms-txt" href="/llms.txt"> to HTML <head>
- Inject generated JSON-LD into page <head> sections
- Merge robots.txt suggestions with existing rules

name	aeo-generate
description	Use when creating llms.txt, JSON-LD structured data, or robots.txt AI crawler configuration for a website or project build output

Generate AI infrastructure files from existing website content to make it discoverable by AI search engines.

File	Purpose
`llms.txt`	Machine-readable site summary for LLMs (llmstxt.org standard)
`llms-full.txt`	Full content version for deep AI consumption
`_aeo/generated-schemas.json`	JSON-LD schemas (Article, FAQPage, BreadcrumbList)
robots.txt suggestions	AI crawler allow/deny rules (printed, not auto-applied)

Identify build output. Ask the user for the directory containing their built site (e.g., dist/, out/, build/). Check for common framework patterns:
- Next.js: .next/ or out/
- Vite/Astro: dist/
- Hugo/Jekyll: public/
Preview first. Run:
```
npx aeoptimize generate <dir> --dry-run
```
Show the user what will be generated and explain each file's purpose.
Confirm and generate. On approval:
```
npx aeoptimize generate <dir>
```
Review generated files. Read each generated file and suggest manual refinements:
- llms.txt: Verify site name, description, and page listing are accurate
- JSON-LD: Check that generated schemas match the actual content
- robots.txt: Explain each AI crawler and let user decide allow/deny
Integration guidance. Explain how to deploy:
- Place llms.txt at site root (alongside robots.txt)
- Add <link rel="llms-txt" href="/llms.txt"> to HTML <head>
- Inject generated JSON-LD into page <head> sections
- Merge robots.txt suggestions with existing rules

aeo-generate