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inventory-content

Systematic cataloging of information assets. Creates comprehensive inventories of all content with metadata and characteristics.

Install with Tessl CLI

npx tessl i github:dandye/ai-runbooks --skill inventory-content
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Content Inventory Skill

Create a systematic catalog of information assets within a specified path. This skill builds a comprehensive inventory including metadata, file characteristics, and format analysis to support content governance and strategic planning.

Inputs

  • PATH - The directory or file path to inventory (e.g., "/documentation")
  • OUTPUT_FORMAT - (Optional) The output format for the inventory, e.g., "csv", "json", "markdown" (default: "json")
  • METADATA_EXTRACTION - (Optional) Boolean, whether to extract deep metadata (author, date, tags) (default: true)
  • FORMAT_ANALYSIS - (Optional) Boolean, whether to analyze file formats and types (default: true)

Workflow

Step 1: Asset Discovery

Recursively scan the PATH to identify all files and assets.

  • Record file paths, names, and sizes.
  • Identify file types (Markdown, HTML, PDF, Image, etc.).

Step 2: Metadata Extraction

If METADATA_EXTRACTION is true, extract metadata from each asset:

  • System Metadata: Creation date, modification date, owner.
  • Embedded Metadata: Frontmatter (YAML), title headers, tags, categories.
  • Content Metrics: Word count, reading time estimation.

Step 3: Format & Structure Analysis

If FORMAT_ANALYSIS is true, analyze the structure:

  • Template Usage: Identify if standard templates are used.
  • Hierarchy Depth: Depth in the directory structure.
  • Resource Dependencies: Images or other assets linked.

Step 4: Inventory Report Generation

Compile the data into a structured inventory format (CSV, JSON, or Markdown Table) as specified by OUTPUT_FORMAT.

Required Outputs

A CONTENT_INVENTORY_REPORT in the specified OUTPUT_FORMAT containing:

  • Asset List: Full list of discovered assets.
  • Metadata Table: Columns for Title, URL/Path, Author, Last Modified, Type, Tags.
  • Summary Statistics: Total count by type, average age, volume by category.

Quick Reference

  • Purpose: Establish a baseline understanding of content assets for governance.
  • Use Case: Migration planning, audit preparation, consolidation projects.
Repository
dandye/ai-runbooks
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