markdown-helper

Token-efficient Markdown parsing extracts headers, tables, and lists directly from files without bloating the context window. This reduces token usage and enables faster interactions when working with large documentation projects.

You can generate Mermaid diagrams from Markdown workflows using local CLI tooling. The Skill leverages mermaid-cli to transform text-based documentation into visual diagrams for real-world documentation projects.

Yes, bulk linting operations use markdownlint-cli2 to auto-fix formatting across single files or broad file patterns. This ensures documentation consistency with minimal token overhead during the scanning process.

Yes, Node.js is a required dependency. The Skill relies on local tooling including marked-cli, mermaid-cli, and markdownlint-cli2, which require Node.js installation and environment configuration setup before execution.

Running a dedicated extraction command pulls headers directly from the Markdown file without loading the entire document. This token-efficient approach quickly scans large specifications like a 1,000-line file to retrieve structural information.

Loading full Markdown files into context directly consumes excessive tokens. Token-efficient parsing manipulates content through local CLI tools instead, extracting only necessary elements like headers and tables to minimize overhead.