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Tyler-R-Kendrick
Tyler-R-KendrickCOMMUNITY
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GitHub

sdlc

Manage multi-phase software workflows with GitHub Stacked PRs and automated closeout.

1|Updated Jul 12, 2026
Search Tags:#automation#workflow#github#sdlc#code-review#stacked-prs
One-click install
npx skills add https://github.com/Tyler-R-Kendrick/slm-training --skill sdlc-tyler-r-kendrick
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sdlc
Source: https://github.com/Tyler-R-Kendrick/slm-training/tree/main/.agents/skills/sdlc
Command: npx skills add https://github.com/Tyler-R-Kendrick/slm-training --skill sdlc-tyler-r-kendrick

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the complexity of managing multi-phase engineering work by enforcing a structured, bottom-up delivery process that prevents "mega-PR" bottlenecks and ensures high-quality, reviewable code.

Core Features & Use Cases

  • Stacked PR Workflow: Automatically manages sequential PR layers using the official GitHub Stacked PRs extension, ensuring foundations are merged before dependents.
  • Automated Closeout: Enforces a mandatory rubber-duck and adversarial review process for every PR, ensuring CI checks and documentation are completed before squash-merging.
  • Autotrain Integration: Coordinates continuous training loops with delivery, ensuring only positive-result iterations are stacked and shipped while maintaining rigorous experiment documentation.

Quick Start

Use the sdlc skill to plan and execute a multi-layer feature implementation by defining the goal and spawning subagents for each stack layer.

Frequently Asked Questions about sdlc

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

FAQPage Schema
How do I manage stacked pull requests for multi-phase feature development?▼

Stacked pull requests for multi-phase feature development are managed by automatically structuring sequential PR layers, ensuring foundational code merges before dependent layers. This enforces a bottom-up delivery process that prevents mega-PR bottlenecks and maintains high code reviewability.

What is the best way to automate the software development lifecycle closeout process on GitHub?▼

Automating the software development lifecycle closeout process involves enforcing mandatory rubber-duck and adversarial review phases for every PR. It ensures CI checks and documentation are completed before squash-merging, providing deterministic delivery and repository-wide invariant enforcement.

How does stacked PR workflow handle continuous training loops and iterative experiments?▼

Stacked PR workflow handles continuous training loops by coordinating autotrain integration with delivery. It ensures only positive-result iterations are stacked and shipped while maintaining rigorous experiment documentation throughout the incremental check-ins.

Can I use this workflow for complex multi-layer architectural changes requiring incremental check-ins?▼

Yes, this workflow applies directly to complex multi-layer architectural changes requiring incremental check-ins. It uses Scalar-based workspace management and GitHub Stacked PRs to satisfy requirements for deterministic delivery and adversarial review.

Why should I use stacked PRs instead of a single large pull request for complex engineering work?▼

Stacked PRs prevent mega-PR bottlenecks by breaking complex engineering work into a structured, bottom-up delivery process. This approach ensures high-quality, reviewable code by enforcing that foundations are merged before their dependents.

Do I need specific extensions to enable automated stacked PR management?▼

Automated stacked PR management requires the official GitHub Stacked PRs extension and Scalar-based workspace management. These dependencies enable the deterministic delivery and multi-layer architectural changes required for the workflow.

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