sdlc-repository-templates

Generate standardized SDLC learning repository structures with artifact templates and validation.

1|Updated Dec 24, 2025
One-click install
npx skills add https://github.com/clostaunau/holiday-card --skill sdlc-repository-templates
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sdlc-repository-templates
Source: https://github.com/clostaunau/holiday-card/tree/main/.claude/skills/sdlc-repository-templates
Command: npx skills add https://github.com/clostaunau/holiday-card --skill sdlc-repository-templates

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a complete template library and structural standards for creating SDLC learning repositories, with consistent folder naming, artifact README templates, and traceability guidance.

Core Features & Use Cases

  • Repository Structure: Standardized folder layout for phases and artifacts.
  • Artifact Templates: README.md templates for artifacts and examples for training.
  • Traceability & Governance: Master trackers and dependency matrices.

Quick Start

Copy an artifact README template and adapt it to your chosen SDLC approach, then link artifacts in the Master Tracker.

Frequently Asked Questions about sdlc-repository-templates

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

FAQPage Schema
How do I create a standardized SDLC repository structure for learning?

Standardized SDLC repository structure uses canonical folder layouts, phase naming conventions, and artifact IDs (PP-AA format) to ensure consistency across methodologies like Agile, DDD, and MBSE. Copy the provided README templates, organize phases and artifacts according to the schema, and populate the Master Tracker to establish traceability across your learning repository.

What's the best way to ensure traceability and consistency in methodology repositories?

Traceability in SDLC repositories is maintained through Master Trackers, dependency matrices, and the link_check.py validation tool. Define artifact relationships, enforce naming conventions, and run validation checks to verify that all artifacts are properly documented and linked, preventing broken dependencies and governance gaps.

Can I apply these repository templates to different SDLC approaches?

Yes. These templates support multiple SDLC approaches including Agile, Domain-Driven Design, Structured Analysis, Model-Based Systems Engineering, and Event-Driven Architecture. Adapt the canonical folder layout and artifact README templates to your chosen methodology while maintaining the PP-AA naming convention and phase structure.

How do I validate repository structure and artifact documentation?

Use the included tools/link_check.py validation tool to automatically check repository structure, verify artifact IDs follow PP-AA format, and ensure all links and references in documentation are correct. This validates consistency across phases, detects broken dependencies, and confirms governance compliance without manual inspection.

What documentation should I include for each artifact in a learning repository?

Each artifact requires a README.md following provided templates that document purpose, methodology context, relationships to other artifacts, and examples. Templates guide content structure for different SDLC approaches, ensuring artifacts are discoverable, consistently formatted, and properly integrated into the Master Tracker and dependency matrices.

Do I need existing methodology knowledge to set up these repository templates?

Basic familiarity with your chosen SDLC approach (Agile, DDD, MBSE, etc.) helps, but the templates guide structure and naming regardless of depth. The canonical layout and artifact examples provide scaffolding; adapt them to your learning context and populate with domain-specific content as your understanding grows.