documentation-specialist

Extract skill metadata into a structured YAML block for indexing.

Updated Feb 5, 2026
One-click install
npx skills add https://github.com/arelben/Goals-Dashboard --skill documentation-specialist-arelben
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: documentation-specialist
Source: https://github.com/arelben/Goals-Dashboard/tree/main/.agent/skills/documentation-specialist
Command: npx skills add https://github.com/arelben/Goals-Dashboard --skill documentation-specialist-arelben

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This metadata unit solves the problem of discovering and indexing skill units by converting their structural content into a precise, machine-readable metadata block that enables consistent search, tagging, and integration across tooling.

Core Features & Use Cases

  • Generates a uniform YAML metadata block from SKILL.md frontmatter and repository structure for discovery and cataloging.
  • Validates mandatory fields (name, description) and captures optional resources (scripts/references/assets) for richer context.
  • Supports automated indexing workflows for PDA-compliant skills, ensuring consistent categorization, dependencies, and safety checks across large repositories.

Quick Start

Describe your documentation goal and I will generate the tailored plan.

Frequently Asked Questions about documentation-specialist

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate structured YAML metadata for skill indexing and discovery?

To generate structured YAML metadata for skill indexing, this tool extracts structural content from SKILL.md frontmatter and repository structures, outputting a machine-readable block with fields like name, tagline, description, and keywords.

What is the best way to validate mandatory fields for PDA-compliant skills?

Validating mandatory fields for PDA-compliant skills involves checking that essential metadata like name and description are present, while capturing optional resources such as scripts, references, and assets to ensure consistent categorization.

Can I use this to catalog both brownfield and greenfield documentation units?

Yes, you can catalog both brownfield and greenfield documentation units. The tool processes structural content from existing repository files and new units to generate uniform metadata for automated indexing workflows.

How does token-optimization work when extracting skill repository metadata?

Token-optimization in metadata extraction works by converting verbose structural content into a precise, machine-readable YAML block, reducing the data footprint required for consistent search, tagging, and integration across tooling.

Do I need existing references or assets to create a uniform metadata block?

You do not need existing references or assets to create a uniform metadata block. The system validates mandatory fields like name and description first, then captures optional resources for richer context if they are available.