This skill provides a comprehensive framework for Claude to evaluate and verify the quality of collected data during research and report generation. It defines strict criteria for source reliability (grading from A to F), data freshness (targeting 2024-2025), and structural completeness for market data, company profiles, and patent analysis. By implementing these standards, users can ensure that AI-driven insights maintain professional-grade accuracy, consistency, and academic integrity, supported by automated verification checklists for cross-chapter alignment.
主な機能
01Source Reliability Grading (Grades A to F)
02Cross-Chapter Data Consistency Verification
03Mandatory Data Field Validation for Market and Patents
049 GitHub stars
05Data Recency Enforcement (2023-2025 window)
06Standardized Table Templates for M&A and Competitiveness