The Prompt-to-Paper framework uses a multi-agent system to generate scientific manuscripts grounded in verifiable literature. It replaces fabricated results with a deterministic retrieval-augmented generation pipeline and section-aware scoring. This approach targets the rigor gap in AI-written research. Practitioners gain a standardized framework to evaluate if automated papers meet actual publication quality.