Documentation

Complete documentation for copyright.sh - including our Creator Guide for content licensing and API Reference for developers building AI applications.

Authentication

All API requests require authentication using Bearer tokens. Include your API key in the Authorization header.

curl -H "Authorization: Bearer sk_live_abc123..."
     https://api.copyright.sh/v1/verify-license

API Key Types

• sk_test_ - Test environment
• sk_live_ - Production environment

Creator Guide

This guide helps content creators understand AI licensing concepts and implement them effectively using copyright.sh.

The Three Pillars of AI Licensing

Every AI license consists of three key components:

• Stage: What phase of AI processing (infer, embed, tune, train)
• Distribution: Whether outputs will be private or public
• Price: What you get paid per 1,000 tokens read (defaults to free but usage is still logged)

<meta name="ai-license" content="allow; distribution:private; price:0.12">

WordPress Integration

The official Copyright.sh WordPress plugin automatically adds AI license meta tags to your posts and pages based on your settings.

AI Stages Explained

Different AI processing stages have different implications for your content. Here's what each stage means:

Core Stages

Train

What it means: Your content becomes part of the dataset used to teach AI models new patterns and knowledge.

Legal context: May be considered fair use in the US but not guaranteed in the EU.

Typical pricing: $0.25-$0.50 per 1K tokens (highest value due to permanent inclusion)

<meta name="ai-license-train" content="allow; distribution:private; price:0.35">

Infer

What it means: AI uses your content to generate real-time responses to user queries.

Usage pattern: Temporary, on-demand access for immediate responses

Typical pricing: $0.05-$0.25 per 1K tokens (depending on distribution)

<meta name="ai-license-infer" content="allow; distribution:private; price:0.10">

Embed

What it means: Your content is converted into mathematical vectors for search and retrieval.

Usage pattern: Semantic search, content recommendation, similarity matching

Typical pricing: $0.05 per 1K tokens (lowest impact on your content)

<meta name="ai-license-embed" content="allow; distribution:public; price:0.05">

Tune

What it means: Fine-tuning and adapting existing models for specific tasks using your content.

Usage pattern: Specialized model adaptation and customization

Typical pricing: $0.15-$0.30 per 1K tokens (higher than inference, lower than training)

<meta name="ai-license-tune" content="allow; distribution:private; price:0.20">

Distribution Guide

Distribution controls whether AI outputs using your content will be kept private or made publicly accessible.

Distribution Options

<meta name="ai-license" content="allow; distribution:private; price:0.08">

<meta name="ai-license" content="allow; distribution:public; price:0.25">

Choosing the Right Distribution

Combined Stage and Distribution Examples

<!-- Block training, allow private inference -->
<meta name="ai-license-train" content="deny">
<meta name="ai-license-infer" content="allow; distribution:private; price:0.10">

<!-- Free private, paid public -->
<meta name="ai-license" content="allow; distribution:private">
<meta name="ai-license" content="allow; distribution:public; price:0.20">

Pricing Strategy Guide

Setting the right price balances fair compensation with encouraging AI innovation. Our research shows creators are successfully charging these rates:

Industry Benchmark Rates (USD per 1K tokens)

Stage-Based Pricing Strategy

Pricing Factors to Consider

• Content quality: Exclusive, well-researched content commands higher rates
• Freshness: Breaking news or cutting-edge research can be priced premium
• Exclusivity: If you're the only source, you have pricing power
• Volume: Consider offering volume discounts for bulk usage
• Competition: Research what similar creators charge

<!-- Encourage adoption with competitive rates -->
<meta name="ai-license" content="allow; distribution:private; price:0.10">

<!-- Different rates by stage and distribution -->
<meta name="ai-license" content="allow; distribution:private; price:0.10">
<meta name="ai-license-train" content="allow; distribution:private; price:1.00">
<meta name="ai-license-infer" content="allow; distribution:public; price:0.25">

<!-- High-value, exclusive content -->
<meta name="ai-license-train" content="allow; distribution:private; price:0.50">
<meta name="ai-license-infer" content="deny">

<!-- Free private, paid public -->
<meta name="ai-license" content="allow; distribution:private">
<meta name="ai-license" content="allow; distribution:public; price:0.25">

Verify License

{
  "url": "https://example.com/article",
  "tokens": 1500,
  "stage": "train",
  "distribution": "private"
}

{
  "licensed": true,
  "rate": 0.05,
  "cost": 0.075,
  "currency": "EUR",
  "license_id": "lic_abc123",
  "creator": {
    "name": "John Smith",
    "verified": true
  },
  "terms_url": "https://copyright.sh/terms"
}

Get Content

Retrieve normalized metadata and the latest licensing directives for a specific URL. This endpoint is ideal for dashboards, preflight checks, and surfacing creator attribution alongside AI usage.

fetch('https://api.copyright.sh/v1/content?url=' + encodeURIComponent('https://example.com/article'), {
  headers: {
    Authorization: 'Bearer sk_live_abc123'
  }
}).then(res => res.json());

{
  "url": "https://example.com/article",
  "title": "Generative AI Licensing Guide",
  "creator": {
    "name": "Jordan Lee",
    "verified": true
  },
  "license": {
    "stage": "infer",
    "distribution": "private",
    "price": 0.08
  },
  "updated_at": "2025-09-18T14:32:00Z"
}

Log Usage

{
  "license_id": "lic_abc123",
  "tokens_used": 1500,
  "hmac_signature": "sha256=abc123...",
  "timestamp": "2025-01-23T10:00:00Z"
}

Webhooks

Subscribe to webhook events to keep your internal systems synchronized with creator preferences and usage receipts in near real time.

Available Events

• usage.logged — fired after a usage record posts to the ledger.
• license.updated — sent when a creator updates pricing, stages, or distribution settings.
• license.revoked — triggered if a creator withdraws access for a URL you previously verified.

Verify Signatures

Webhook payloads use the same HMAC signature scheme as the REST API. Compare the x-cs-signature header against a locally generated hash.

import hmac
import hashlib
import json

def verify_webhook(payload: dict, signature: str, secret: str) -> bool:
    message = json.dumps(payload, sort_keys=True)
    expected = hmac.new(secret.encode(), message.encode(), hashlib.sha256).hexdigest()
    return hmac.compare_digest(f"sha256={expected}", signature)

See /docs-api.html#webhooks for payload schemas, testing utilities, and replay attack guidance.

HMAC Verification

All usage logging requires HMAC signatures for security and tamper-proofing.

Python Example

import hmac
import hashlib
import json

def create_hmac_signature(payload, secret_key):
    message = json.dumps(payload, sort_keys=True)
    signature = hmac.new(
        secret_key.encode('utf-8'),
        message.encode('utf-8'),
        hashlib.sha256
    ).hexdigest()
    return f"sha256={signature}"

# Usage
payload = {
    "license_id": "lic_abc123",
    "tokens_used": 1500,
    "timestamp": "2025-01-23T10:00:00Z"
}
signature = create_hmac_signature(payload, "your_secret_key")

Rate Limits

Rate limits protect creators and maintain reliable performance for every integration. Limits are enforced per API key.

Python SDK

The Python SDK will provide:

• Simple client initialization with API keys
• License verification and validation
• Usage logging with HMAC signatures
• Automatic retry logic and error handling
• Type hints and comprehensive documentation

Expected release: Q1 2025. Contact us for early access.

JavaScript SDK

The JavaScript SDK will provide:

• Browser and Node.js compatibility
• TypeScript definitions included
• Promise-based async operations
• Automatic token counting utilities
• Built-in caching for license lookups

Expected release: Q1 2025. Contact us for early access.

Go SDK

The Go SDK will provide:

• Idiomatic Go interfaces
• Concurrent request handling
• Context support for cancellation
• Efficient memory usage
• gRPC support for high-performance applications

Expected release: Q2 2025. Contact us for early access.

Error Handling

The API returns standard HTTP status codes and detailed error messages.