prompt-refinement

Prompt refinement and workflow orchestration for Codex: turn vague ideas into scoped goals, reviewable SPECs, validation evidence, and PR-ready handoffs.

Retrieval-grounded prompt refinement as a Python library, CLI, and MCP server

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 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.

A meta-prompt that refactors any LLM prompt into a clearer, more structured, and higher-performing version using proven prompt engineering techniques.

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.

Codex插件，能将图片沉淀为可复用的视觉记忆，助你持续创作出美学风格一致的图片。The Codex plugin can turn images into reusable visual memories, helping you consistently create images with a unified aesthetic style.

MCP server that refines your coding prompts with real codebase context before your AI agent acts on them.

Automated prompt refinement pipeline that iteratively optimises LLM classification prompts using a classifier → evaluator → optimiser loop, targeting precision and recall thresholds on Azure OpenAI.

Collaborative prompt refinement tool - AI asks questions, you provide answers, together you build better prompts

Intelligent token optimization tool for AI and cloud code. Cut token costs by up to 75% while maintaining top performance. Essential for developers in 2026.

Context-aware prompt refinement for Pi using GPT-5.6 Luna through a Codex subscription.

A Codex skill for refining requests into actionable prompts while preserving intent, constraints, and authorization.

MMPS - Multi-Modal Prompt Structuring System

A framework for distilling abstract structures and presenting them with precise language. For precision prompting and communication.

Esercizio Lezione 01 - AI Coding Upskilling: refinement di un prompt vago in una richiesta più controllabile e verificabile.

Nam-Cheol/namba-ai → AI Work Manager: Turn Vague Ideas into PR-Ready Specs & Evidence 2026