PromptForge

What it does

A production-ready Python CLI that runs a multi-agent sequential pipeline via Ollama to generate self-contained master prompts optimized for AI code editors (Cursor, Claude Code, Windsurf, GitHub Copilot). Turn an app idea into a copy-pasteable prompt containing architecture diagrams, implementation plan, business impact analysis, bottleneck detection, security audit, AI strategy recommendations, and a technology radar — all in one shot.

Contribute to BharathR1703/PromptForge development by creating an account on GitHub.

A production-ready Python CLI that runs a multi-agent sequential pipeline via Ollama to generate self-contained master prompts optimized for AI code editors (Cursor, Claude Code, Windsurf, GitHub Copilot). Turn an app idea into a copy-pasteable prompt containing architecture diagrams, implementation plan, business impact analysis, bottleneck detection, security audit, AI strategy recommendations, and a technology radar — all in one shot. pip install ollama rich python master_prompt_generator.py Choose a mode from the menu, enter your idea, pick a model, and PromptForge runs the pipeline. Output is printed in a Rich terminal UI and can be saved as markdown, JSON, or copied to clipboard.…from github.com

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  PromptForge2025 · github.com · ▲474

  PromptForge: Open-source AI prompt engineering workbench with systematic evaluation I built PromptForge after getting frustrated with the manual trial-and-error approach to prompt engineering. Most tools are just text editors, but I wanted something that brings software engineering discipline to prompt development. Key technical features: - AI-assisted prompt generation (stop starting from scratch) - Systematic evaluation engine that auto-generates test suites - Multi-model support (Claude, GPT-4, Azure OpenAI) - Go backend with SQLite for performance and simplicity - One-line Docker…

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  Hi HN, I recently built PromptForge — a minimal, developer-first web app that helps you generate high-quality GPT prompts from just a few structured fields. Why? As a developer, I often found myself rewriting similar prompts manually. I wanted a faster and more reliable way to generate optimized prompts for various tasks — coding, debugging, idea generation, etc. So I built a tool that combines structure, speed, and simplicity. What it does: Select a use case (e.g. summarization, code explanation) Fill out a few fields (context, tone, output format) Get a clean, optimized prompt Save, reuse,…

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