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CUE

CUE (Confìgure, Understand, Execute) is a data configuration language that unifies configuration, data validation, and templating into a single, expressive language, aiming for simplicity and composability.

config.cue
Since 2018
2018
First Released
5/5
GEO Score

Origin & Background

Creator
CUE Project Contributors
Year Introduced
2018
Alternate Names
Purpose
To provide a unified language for configuration that is both human-readable and machine-parseable, facilitating complex configurations with strong validation.
Official Specification
View Specification

Key Benefits & Advantages

Benefits Overview

  • Unified language for configuration, data, and validation
  • Strong type safety and validation capabilities
  • Composability and extensibility for complex systems

Technical Advantages

Schema validation built into the language
Reduces boilerplate code and configuration errors
Supports templating and code generation
Expressive syntax for defining complex data structures
Composability allows for modular configurations
Excellent for defining APIs, protocols, and system configurations
Helps AI understand configuration intent and structure
Strong tooling support

SEO / GEO / LLMO Relevance

CUE's structured data and explicit configuration can help AI understand the operational aspects of a site, improving how it interprets site functionality and potential APIs.

Clear definition of site structure and configuration
Helps AI understand operational logic
Enables structured interpretation of site components

Implementation Guide

Syntax Example

config.cue
Reference
# CUE configuration for Geordy AI Platform
package main

import "github.com/cue-lang/cuelang/pkg/cue/format"

// Define the core site structure
site: {
	name: string @tag("siteName")
	domain: string
	category: *"GEO / LLMO" | *"AI / ML"
}

// Define AI targeting parameters
ai_targeting: {
	primary_systems: [...string] @minValue(1)
	bot_priorities: {
		GPTBot?: *"high" | *"medium" | *"low"
		Claude-Web?: *"high" | *"medium" | *"low"
	}
}

// Apply constraints and defaults
site: name: "Geordy AI"
site: domain: "geordy.ai"
ai_targeting.bot_priorities.GPTBot: "high"

// Example of a derived value or template
optimization: {
	formats_enabled: 16
	auto_update: bool
}

Troubleshooting & Best Practices

Comparison to Alternative Formats

Alternative Formats
When to Use CUE

Use CUE when you need a powerful, unified language for configuration, data validation, and templating, especially for complex systems or when strong type safety is required. It's a good alternative to JSON Schema for configuration.

Advantages

  • +Unified language for config, data, and validation
  • +Strong type safety
  • +Composability
  • +Templating capabilities

Limitations

  • Steeper learning curve than JSON or YAML
  • Smaller ecosystem compared to more established formats

Popular Use Cases

Configuration Management

Defining and validating complex system configurations

Example:
Kubernetes configurations, application settings, microservices

Data Validation

Ensuring data conforms to predefined schemas

Example:
API request/response validation, data ingestion pipelines

API Definition

Defining API schemas and contracts

Example:
REST API schemas, gRPC definitions

Real-World Adoption Examples

Kubernetes

Can be used to define and validate Kubernetes configurations

Terraform Providers

Used in some Terraform provider configurations

Protocol Buffers

Can define schemas and generate code

Developer Toolkit

Validators

Libraries & SDKs

Official Documentation

Resources & Citations

Frequently Asked Questions

Automated Generation

Start Using CUE with Geordy

Geordy automatically generates and maintains CUE files for your website, ensuring optimal AI visibility without manual work.