ComplexityLevel Decorator¶

Specifies the permitted complexity level for the implementation.

Category: Implementation-Focused

Parameters¶

Parameter	Type	Description	Default
`code`	`enum`	Code complexity limit	`moderate`
`concepts`	`enum`	Conceptual complexity limit	`intermediate`
`dependencies`	`enum`	External dependency usage	`standard`

Code Options¶

simple: Use simple, straightforward code structures. Avoid complex algorithms or patterns.
moderate: Balance simplicity with efficiency. Use standard patterns where appropriate.
complex: Optimize for performance and scalability. Use advanced patterns when beneficial.
necessary-only: Use only the complexity that is absolutely necessary for the task.

Concepts Options¶

beginner-friendly: Use only basic concepts that beginners would understand. Explain any non-trivial concepts.
intermediate: You can use intermediate-level concepts that most practitioners would be familiar with.
advanced: You can use advanced concepts and techniques appropriate for experienced developers.

Dependencies Options¶

none: Do not use any external dependencies or libraries.
minimal: Use only essential dependencies. Prefer standard libraries when possible.
standard: Use common, well-established dependencies as needed.
whatever-needed: Use any dependencies that would make the implementation better, regardless of number.

Examples¶

Simple date formatter with beginner-friendly concepts¶

+++ComplexityLevel(code=simple, concepts=beginner-friendly, dependencies=minimal)
Implement a simple date formatter utility that converts between different date formats without external libraries.

The model will provide a simple date formatter implementation using only basic programming concepts and minimal dependencies, suitable for beginners.

Complex algorithm with standard dependencies¶

+++ComplexityLevel(code=complex, concepts=advanced, dependencies=standard)
Implement a machine learning algorithm for sentiment analysis.

The model will provide an optimized, advanced implementation using standard libraries and frameworks appropriate for experienced developers.

Model-Specific Implementations¶

gpt-4-turbo¶

Instruction: Implement this with the following complexity constraints: {code_complexity}, {concept_complexity}, {dependency_usage}.

Notes: More explicit phrasing works better with this model.

Implementation Guidance¶

Web development task¶

Original Prompt:

Create a function to validate email addresses.

Transformed Prompt:

Please implement this with appropriate complexity constraints. Use simple, straightforward code structures. Avoid complex algorithms or patterns. Use only basic concepts that beginners would understand. Explain any non-trivial concepts. Use only essential dependencies. Prefer standard libraries when possible.

Create a function to validate email addresses.

Notes: The transformed prompt guides the model to create a simple implementation with minimal dependencies that would be understandable to beginners.

Transformation Details¶

Base Instruction: Please implement this with appropriate complexity constraints.

Placement: prepend

Composition Behavior: override

Parameter Effects:

code:
When set to simple: Use simple, straightforward code structures. Avoid complex algorithms or patterns.
When set to moderate: Balance simplicity with efficiency. Use standard patterns where appropriate.
When set to complex: Optimize for performance and scalability. Use advanced patterns when beneficial.
When set to necessary-only: Use only the complexity that is absolutely necessary for the task.
concepts:
When set to beginner-friendly: Use only basic concepts that beginners would understand. Explain any non-trivial concepts.
When set to intermediate: You can use intermediate-level concepts that most practitioners would be familiar with.
When set to advanced: You can use advanced concepts and techniques appropriate for experienced developers.
dependencies:
When set to none: Do not use any external dependencies or libraries.
When set to minimal: Use only essential dependencies. Prefer standard libraries when possible.
When set to standard: Use common, well-established dependencies as needed.
When set to whatever-needed: Use any dependencies that would make the implementation better, regardless of number.

Compatibility¶

Requires: None
Conflicts: None
Compatible Models: gpt-4-turbo, gpt-4o, claude-3-7-sonnet-latest, llama-3.2
Standard Version: 1.0.0 - 2.0.0

LanguagePreference: Enhances ComplexityLevel ComplexityLevel works well with LanguagePreference to specify both the programming language and its complexity level.
OptimizationFocus: Conflicts with ComplexityLevel May conflict with OptimizationFocus if that decorator requests optimizations that would increase complexity beyond the specified level.