Markdown Document Sharder
Splits large Markdown files into organized, manageable sections based on level 2 headers.
The bmad-shard-doc skill optimizes large documentation files by programmatically exploding them into smaller, focused shards using the @kayvan/markdown-tree-parser. Part of the BMAD (Breakthrough Method for Agile AI Driven Development) framework, it automates the process of identifying H2 sections, creating structured destination folders, and generating an index file. This approach is essential for modern AI-driven development workflows, as it prevents context window bloat and allows Claude to interact with specific documentation segments more accurately and efficiently.
주요 기능
01Automated splitting based on level 2 Markdown headers
02Smart destination folder management and creation
03Generates index.md for easy navigation of sharded content
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05Configurable cleanup options: delete, archive, or keep original
06Integrity verification to ensure all sections are correctly processed
사용 사례
01Managing massive technical specifications by sharding content into manageable files
02Decomposing monolithic architecture documents for better AI context management
03Converting large READMEs into modular project documentation structures