Black SparrowBlack Sparrow

CLI Reference

Commands: check-ai & schema

Audit website readiness for AI search engines (/llms.txt) and validate schema.org structured data.

As search evolves toward conversational AI answers and rich snippet search results, Black Sparrow provides two specialized commands to optimize your digital footprint: check-ai and schema.

1. sparrow check-ai — AI Search Readiness (GEO)

Generative Engine Optimization (GEO) ensures that AI search engines (like ChatGPT Search, Perplexity, Claude, and Google AI Overviews) can discover, comprehend, and cite your website.

Terminal
Terminal
sparrow check-ai <URL>

What check-ai Probes

  • 📄 /llms.txt Discovery: Checks if /llms.txt and /llms-full.txt exist at the domain root, providing clean Markdown documentation for AI systems.
  • 🤖 AI Bot Permissions: Analyzes robots.txt rules specifically for leading AI crawler user agents:
    • GPTBot (OpenAI / ChatGPT)
    • ClaudeBot (Anthropic / Claude)
    • PerplexityBot (Perplexity AI)
    • Google-Extended (Gemini training)
    • Applebot-Extended (Apple Intelligence)
  • 🛡️ WAF & Firewall Screens: Tests whether Cloudflare, Akamai, or DataDome bot challenge screens intercept AI crawlers with HTTP 403 or JavaScript puzzles.

Example

Terminal
Terminal
sparrow check-ai https://example.com

Sample output:

================================================================================
                         AI SEARCH & GEO AUDIT
================================================================================
Target URL       : https://example.com
 
LLMS.TXT DISCOVERY:
  /llms.txt      : [FOUND] (200 OK, 1.4 KB) - Valid structure
  /llms-full.txt : [FOUND] (200 OK, 12.8 KB)
 
AI ROBOTS.TXT DIRECTIVES:
  GPTBot         : [ALLOWED]
  ClaudeBot      : [ALLOWED]
  PerplexityBot  : [ALLOWED]
  Google-Extended: [DISALLOWED] (Opted out of Gemini training)
 
BOT DEFENSE (WAF):
  Status         : Clean. No Cloudflare or Akamai challenge screens detected.
 
VERDICT:
  Overall Readiness : HIGH (Ready for AI citations & indexing)

2. sparrow schema — Schema.org & Google Rich Results

Structured data helps search engines understand products, reviews, FAQs, and recipes, triggering rich result badges and star ratings in Google search.

Terminal
Terminal
sparrow schema <URL> [OPTIONS]

What schema Validates

  • 📐 JSON-LD & Microdata Syntax: Extracts and checks syntax of all inline schema scripts.
  • ⭐ Google Rich Results Requirements: Checks required and recommended properties against Google's official Search Central guidelines for:
    • Article & BlogPosting (headline, image, datePublished, author)
    • Product (name, image, offers, price, availability, aggregateRating)
    • BreadcrumbList (itemListElement, position, item)
    • FAQPage (mainEntity, Question, AcceptedAnswer)
    • LocalBusiness & Organization (name, address, telephone, logo)
    • Recipe & Event

Example

Terminal
Terminal
sparrow schema https://example.com/products/running-shoes

Sample output:

================================================================================
                       STRUCTURED DATA AUDIT (SCHEMA.ORG)
================================================================================
URL              : https://example.com/products/running-shoes
Schema Found     : JSON-LD (Product, BreadcrumbList)
 
VALIDATION RESULTS:
  [OK] Product:
    - name             : "Velocity Pro Running Shoes"
    - image            : https://example.com/shoes.png
    - offers.price     : "129.99"
    - offers.currency  : "USD"
    - availability     : "https://schema.org/InStock"
 
  [WARNING] Product:
    - Missing recommended field: "aggregateRating" (Eligible for star rating badges)
    - Missing recommended field: "review"
 
Eligible for Google Rich Results : YES (Product Snippet)