Prompt Decorators
Enhance and standardize prompts for Large Language Models (LLMs) through composable decorators with this framework.
About
Prompt Decorators is a framework designed to standardize and enhance Large Language Model (LLM) prompts using composable decorators. Featuring an official specification and Python reference implementation, it allows users to modify LLM behavior through simple annotations, promoting consistency and reusability across different platforms. By offering a systematic approach to prompt engineering, this framework addresses the challenges of inconsistency, verbosity, and cognitive overhead, making prompt crafting more modular and maintainable, while also integrating with tools like Claude Desktop through its MCP server integration.
Key Features
- Parameter validation and type checking
- Automatic documentation generation
- Registry-based decorator management
- Comprehensive library of 140+ pre-built decorators
- MCP Server integration for desktop AI applications
- 14 GitHub stars
Use Cases
- Crafting prompts for specific reasoning patterns
- Structuring outputs in particular formats
- Ensuring consistent responses across different models
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