xhs-spec

Locate SKILL.md files and extract metadata into a YAML manifest.

43|1|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/liyown/XHSSpec --skill xhs-spec
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xhs-spec
Source: https://github.com/liyown/XHSSpec/tree/main
Command: npx skills add https://github.com/liyown/XHSSpec --skill xhs-spec

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

XHSSpec Skills provide a standardized, discoverable way to identify, parse, and catalog Skill Units defined by SKILL.md frontmatter at repository roots. Each Skill Unit becomes a self-contained metadata entry, including its name, description, and optional resources, enabling consistent discovery and reuse.

Core Features & Use Cases

  • Discover Skill Units by the mandatory SKILL.md frontmatter at root and parse name/description.
  • Aggregate metadata across units to support search, discovery, and automation pipelines.
  • Attach optional resources (scripts/, references/, assets/) to extend capabilities when present.

Quick Start

Scan all Skill Units and generate a metadata entry for each.

Frequently Asked Questions about xhs-spec

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

FAQPage Schema
How do I parse YAML frontmatter from SKILL.md files to generate repository metadata?

To parse YAML frontmatter from SKILL.md files, locate the file at the repository root and validate its metadata. This process extracts the name, description, and optional resources to form a standardized manifest for indexing.

What is a standardized way to discover and catalog Skill Units across a repository?

A standardized way to discover Skill Units is scanning for mandatory SKILL.md files at repository roots. Validating the YAML frontmatter in each file allows you to catalog units with their path, name, description, and references.

Can I include optional resources like scripts and references when extracting YAML metadata for AI workflows?

Yes, you can include optional resources when extracting YAML metadata. The process attaches directories like scripts, references, and assets to each Skill Unit entry, extending capabilities for AI workflow automation and discovery.

How do I return structured YAML documents listing repository Skill Units for indexing?

You return structured YAML documents by identifying every Skill Unit via SKILL.md and extracting its metadata. The output lists each unit with its path, name, description, and references specifically for indexing and discovery.

What happens if a SKILL.md file is missing valid YAML frontmatter during repo automation?

If a SKILL.md file is missing valid YAML frontmatter, it fails validation and is not recognized as a Skill Unit. The discovery process skips it, ensuring only properly defined metadata entries form the standardized manifest.