Framework for systematically navigating AI through complete end-to-end scientific research, from raw data to comprehensive, transparent, human-verifiable research papers. Guides interacting LLM and rule-based agents through conventional scientific paths including data annotation, hypothesis creation, literature search, code writing and debugging, result interpretation, and step-by-step paper writing. Enhances transparency, traceability, and verifiability while allowing scientist oversight.