damage-estimating

Name: damage-estimating
Availability: InStock
Author: collisionengineers

Validate SKILL.md frontmatter and extract structured metadata from Skill units.

Updated May 26, 2026

Search Tags:#automation #documentation #yaml #metadata #frontmatter #repository-analysis #skill-unit

Ready to run

npx skills add https://github.com/collisionengineers/ccc --skill damage-estimating-collisionengineers

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: damage-estimating
Source: https://github.com/collisionengineers/ccc/tree/main/src/skills/damage-estimating
Command: npx skills add https://github.com/collisionengineers/ccc --skill damage-estimating-collisionengineers

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires reportlab, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill identifies valid Skill units in a repository by validating the presence of a root SKILL.md with the required YAML frontmatter and extracts a structured entry describing the Skill for tooling and discovery.

Core Features & Use Cases

Validates Skill units by enforcing the mandatory frontmatter fields (name and description) and the presence of SKILL.md at the unit root.
Collects optional resources references, scripts, and assets as declared, and emits a consistent metadata payload for cataloging and automation.
Produces discovery-ready metadata for automated validation, search indexing, and downstream tooling across large codebases.

Quick Start

Identify Skill units in a repository and emit standardized metadata for each valid Skill using the SKILL.md frontmatter as the source of truth.

Frequently Asked Questions about damage-estimating

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

FAQPage Schema

How do I extract YAML frontmatter metadata from SKILL.md files for automated validation?▼

Extract YAML frontmatter metadata from SKILL.md files by validating mandatory fields like name and description, then generating a structured YAML schema with keywords, dependencies, and components for automated validation and discovery.

What's the best way to validate Skill units in a repository across large codebases?▼

Validate Skill units in a repository by checking for a root SKILL.md file with required YAML frontmatter. This ensures consistent discovery across large codebases by outputting a standardized metadata payload for search indexing and tooling.

How does repository analysis identify valid Skill units and their optional resources?▼

Repository analysis identifies valid Skill units by verifying the SKILL.md frontmatter and mandatory fields. It collects optional resources, scripts, and assets as declared, emitting a consistent metadata payload for cataloging and automation.

Do I need specific dependencies to generate structured YAML schemas from repository metadata?▼

Generating structured YAML schemas from repository metadata requires the reportlab dependency. The process verifies mandatory fields and optional resources, outputting schemas with name, complexity, category, keywords, dependencies, components, and toxicity data.

Can I use extracted metadata for search indexing and downstream tooling across multiple projects?▼

Extracted metadata can be used for search indexing and downstream tooling across projects. The Skill produces discovery-ready metadata by validating SKILL.md frontmatter and emitting a consistent structured payload for automated validation and cataloging.

What mandatory YAML frontmatter fields are required to identify a valid Skill unit?▼

Mandatory YAML frontmatter fields required to identify a valid Skill unit are name and description. The Skill verifies these fields alongside the presence of a root SKILL.md file to ensure consistent discovery across projects.