extract

To extract a research methodology framework from a document, you need a tool that reverse-engineers implicit analytical knowledge by identifying core dimensions like macro drivers and risk validation, then structuring them into reusable templates.

Yes, you can generate reusable prompt templates from market analysis reports by parameterizing the extracted analytical frameworks, which transforms implicit research logic into ready-to-use Agent prompt templates for future studies.

Framework extraction is the process of reverse-engineering research methodologies from in-depth documents to standardize knowledge management, allowing you to capture underlying analytical structures and apply them to future research tasks.

To standardize research methodology across multiple market studies, extract core analytical dimensions such as asset classification, driver logic, and expert opinions from a completed report, then apply the parameterized template to future analyses.

Yes, this approach works for AI agent prompt engineering by structuring the extracted analytical frameworks into parameterized templates, enabling agents to consistently apply rigorous research methodology to analytical tasks.

The limitations of extracting analytical frameworks include the requirement for in-depth, structured source documents to analyze; without clear core dimensions like driver logic and validation, the extracted templates may lack analytical rigor.