Research-lint is a specialized validation tool designed for AI-augmented development workflows using the AIWG framework. It audits research repositories—specifically those within the .aiwg/research/ directory—to detect critical issues such as broken cross-references, missing frontmatter metadata, duplicate identifiers, and orphan notes. By enforcing a strict ruleset that includes ISO 8601 date compliance and GRADE quality assessments, it ensures that your research corpus remains a high-quality, queryable asset for both AI agents and human developers, preventing knowledge decay in complex cognitive architectures.
主な機能
01Integrated GRADE quality assessment validation
02Detection of broken internal and external citations
03146 GitHub stars
04Auto-fixing for missing frontmatter fields and date formatting
05Automated structural integrity checks for research notes
06CI/CD compatibility with configurable severity thresholds
ユースケース
01Automating quality gates in a collaborative research pipeline
02Identifying disconnected information through orphan note detection
03Maintaining a clean and searchable knowledge base for AI agents