AI Preferences (AIPREF)
Machine-readable AI access policies for autonomous agents
Overview
AIPREF is an IETF standard for expressing AI access preferences in machine-readable format. Similar to robots.txt for web crawlers, AIPREF allows websites to declare policies for AI agent access, scraping permissions, and usage terms.
Originary extends AIPREF with PEAC-Receipt verification, enabling sites to enforce policies cryptographically. Agents discover policies via /.well-known/aipref.json, and Originary issues receipts proving policy compliance.
AIPREF File Format
Example /.well-known/aipref.json
{
"version": "1.0",
"ai_access": {
"scraping": "allowed_with_attribution",
"training": "prohibited",
"commercial_use": "requires_license"
},
"rate_limits": {
"requests_per_hour": 100
},
"payment": {
"required": true,
"endpoint": "https://api.example.com/payment"
},
"attribution": {
"required": true,
"format": "Source: example.com"
}
}Use Cases
Content Licensing
Publishers declare licensing terms for AI training data. Agents discover terms and obtain licenses before scraping.
Rate Limiting
Sites declare acceptable request rates. Agents respect limits to avoid being blocked or incurring overage fees.
Attribution Requirements
Content creators specify attribution formats. Agents include proper citations when using content.
Implementation with Originary
Originary reads your aipref.json file and enforces policies at the edge. When agents comply with policies (e.g., by paying required fees), Originary issues PEAC-Receipts that prove compliance.
Agent Request with Policy Compliance
GET /content HTTP/1.1 Host: example.com PEAC-Receipt: eyJhbGc...policy-compliance-proof User-Agent: MyAgent/1.0
Benefits for Publishers
- Machine-readable AI access policies
- Cryptographic enforcement of licensing terms
- Automated compliance verification
- Monetization of AI training data
- Standards-based approach compatible with IETF specifications