Document Audit & Extraction

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Audits document repositories to extract metadata, classify content types, evaluate documentation quality, and build structured inventories.

Document Audit & Extraction provides a structured framework for analyzing and organizing document repositories across four distinct phases: inventory, classification, evaluation, and feature extraction. It automates YAML frontmatter parsing, statistical reporting, cross-reference relationship mapping, and gap analysis. This skill helps teams maintain high documentation standards by programmatically scoring document quality, detecting orphaned pages, highlighting missing sections, and extracting actionable structured data from unstructured Markdown and text files.

Key Features

01Automated multi-format document inventory and statistical reporting
02Weighted quality scorecard with automated health and completeness checks
03Rule-based document classification across guides, ADRs, references, and skills
04Metadata and structured feature extraction from Markdown and YAML frontmatter
0517 GitHub stars
06Cross-reference link mapping and orphaned file gap analysis

Use Cases

01Standardizing repository documentation and identifying coverage gaps or broken links
02Auditing technical documentation and knowledge bases prior to major releases
03Building automated content inventories and metadata catalogs for knowledge architecture