Because consuming content with AI shouldn't be complicated
Codename: RSS 3.0, Make America RSS Again.
- A pattern for AI bots to consume RSS feeds
- Standard XML-based feeds with AI-specific metadata
- A simple way for AI to access machine-readable content
- Based on RSS 2.0: Use XML and HTTP for delivery
- A framework or library you install
- A new technology or language
- A specific company's product
- An additional abstraction in any way
π‘ RIZZ simply says: "AI bots should access content through plain RSS feeds using patterns we've used for decades, with AI tweaks via namespaces."
That's it. Just a pattern. β¨
- Every update is an AI-ready
<item> - Every feed is a single XML file
- Every AI bot is welcome
- Every publisher is open to extend
<rss>: Root with version="2.0"<channel>: Feed metadata (title, link, description)<item>: Content updates (title, link, description, pubDate)
Use the ai: namespace (xmlns:ai="http://xai.org/RIZZ-namespace") for AI metadata:
<ai:model>: Compatible AI models (e.g.,<ai:model>Grok, GPT</ai:model>)<ai:context>: AI prompt or context (e.g.,<ai:context>Summarize for AI developers</ai:context>)<ai:dataQuality>: Data quality score (e.g.,<ai:dataQuality>85</ai:dataQuality>, 0-100)
- Free to use
- Open source (MIT license)
- No vendor lock
- Community driven
- Any AI model supported
- XML-based
- Standard HTTP
- Zero dependencies
- No new tech needed
- Any AI bot
- Any content type
- Any platform
- Simple HTTP GET requests to fetch
/RIZZ.xml - XML payloads with standard RSS 2.0 structure
- Works with any XML parser or HTTP client
- No special endpoints or authentication required (optional HTTP auth)
- AI bots poll the feed URL periodically
- Optional WebSub (Pubsubhubbub) for push notifications
- Low overhead, no vendor lock-in
- Use
<ai:model>to filter compatible models (e.g., only process if "Grok" is listed) - Use
<ai:context>to guide actions (e.g., summarize, analyze, or train) - Use
<ai:dataQuality>to prioritize high-quality data (e.g., >80 for training)
- Real-time news analysis for AI assistants
- Training data collection for machine learning models
- Contextual prompts for conversational bots
- Fetch Feed:
GET /RIZZ.xml - Parse XML with standard RSS 2.0 elements
- Check
<ai:model>,<ai:context>, and<ai:dataQuality>for AI-specific actions
import requests
from xml.etree import ElementTree as ET
# Fetch RIZZ feed
response = requests.get("https://example.com/RIZZ.xml")
root = ET.fromstring(response.content)
# Process each item
for item in root.findall('.//item'):
title = item.find('title').text
ai_model = item.find('.//ai:model', namespaces={'ai': 'http://xai.org/RIZZ-namespace'})
ai_context = item.find('.//ai:context', namespaces={'ai': 'http://xai.org/RIZZ-namespace'})
ai_quality = item.find('.//ai:dataQuality', namespaces={'ai': 'http://xai.org/RIZZ-namespace'})
if ai_model and "Grok" in ai_model.text: # Check compatibility
if ai_quality and int(ai_quality.text) > 80: # Prioritize high-quality data
context = ai_context.text if ai_context else "Process normally"
print(f"Processing: {title} - {context}")
# Perform AI action (e.g., summarize, analyze)Use standard HTTP auth (e.g., Basic or Bearer tokens) in headers:
GET /RIZZ.xml
Authorization: Bearer your-token-hereNo special endpoints neededβkeep it simple and HTTP-based.
Use <ai:model> to limit content to specific AI models (e.g., safe or compatible models only).
Use <ai:dataQuality> to ensure only high-quality data is consumed (e.g., >70 for safe training).
<item>
<title>Safe AI Update</title>
<ai:model>Grok, SafeGPT</ai:model> <!-- Only safe or compatible models -->
<ai:dataQuality>95</ai:dataQuality> <!-- High-quality, trusted data -->
</item>- Enhance semantic richness and interoperability of RSS feeds.
- Provide structured data that can be easily interpreted by AI bots and other systems.
- Embed JSON-LD within the
<item>elements to provide additional structured data.
<rss version="2.0" xmlns:ai="http://xai.org/RIZZ-namespace">
<channel>
<title>AI News Feed</title>
<link>https://example.com/ai-news</link>
<description>AI updates for bots</description>
<item>
<title>AI Reasoning Breakthrough</title>
<link>https://example.com/news/reasoning</link>
<description>New AI logic techniques.</description>
<pubDate>Mon, 10 Mar 2025 01:45:00 EDT</pubDate>
<ai:model>Grok, GPT</ai:model>
<ai:context>Summarize for developers</ai:context>
<ai:dataQuality>90</ai:dataQuality>
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "AI Reasoning Breakthrough",
"url": "https://example.com/news/reasoning",
"datePublished": "2025-03-10T01:45:00-04:00",
"description": "New AI logic techniques.",
"author": {
"@type": "Organization",
"name": "Example News"
},
"aiModel": ["Grok", "GPT"],
"aiContext": "Summarize for developers",
"aiDataQuality": 90
}
</script>
</item>
</channel>
</rss>- Lightweight and familiar: Builds on decades of RSS use.
- AI-ready: Adds just enough metadata for bots without complexity.
- Open and free: No lock-in, no barriers for developers or bots.
RIZZ Discord: fictional
Enjoy using RIZZ! π
RIZZ is an open-source protocol launched under the MIT license by xAI, inspired by SLOP's simplicity for AI integration.