Retrieval-grounded prompt refinement as a Python library, CLI, and MCP server
Automated prompt refinement pipeline that iteratively optimises LLM classification prompts using a classifier → evaluator → optimiser loop, targeting precision and recall thresholds on Azure OpenAI.
A universal, client-side AI prompt engineering tool that enhances your prompts using local or cloud-based AI models. Transform basic prompts into detailed, professional-grade instructions without sending your data to third-party servers.
MCP server that refines your coding prompts with real codebase context before your AI agent acts on them.
A collaborative LLM system that uses OpenAI and Google Gemini to iteratively refine prompts until both models agree on the quality. Features file I/O, markdown comparison, and robust error handling.
Collaborative prompt refinement tool - AI asks questions, you provide answers, together you build better prompts
Claude Code skill that silently refines every prompt for better results (auto mode) and lets you generate optimized prompts as text with /optimize (manual mode)
A framework for distilling abstract structures and presenting them with precise language. For precision prompting and communication.
MMPS - Multi-Modal Prompt Structuring System
Add a description, image, and links to the prompt-refinement topic page so that developers can more easily learn about it.
To associate your repository with the prompt-refinement topic, visit your repo's landing page and select "manage topics."