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sdlc

Orchestrates the full software development lifecycle from branch creation to pull request delivery.

1|Updated Mar 12, 2026
Search Tags:#git#workflow#testing#code review#pull request#github#sdlc
One-click install
npx skills add https://github.com/dwayneparton/claude --skill sdlc-dwayneparton
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sdlc
Source: https://github.com/dwayneparton/claude/tree/main/skills/sdlc
Command: npx skills add https://github.com/dwayneparton/claude --skill sdlc-dwayneparton

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Coding tasks often lack a consistent process, leading to skipped tests, messy branches, and unreviewed changes. This Skill enforces a structured, step-by-step workflow for every code change so features, fixes, and refactors are delivered as review-ready pull requests. ## Core Features & Use Cases - Size-Based Workflow Scaling: Gauges each task as Small, Standard, or Large and applies only the ceremony the blast radius warrants. - Agent Orchestration: Delegates requirements analysis and planning to specialized agents, then runs test-coverage, simplify, and github-pr skills before delivery. - Strict Quality Gates: Forbids skipped tests, requires atomic commits, and never merges PRs — everything is delivered for human review. - Use Case: Ask to implement a new API endpoint. The Skill creates a feature branch, analyzes requirements, plans the implementation, writes tested code, cleans it up, and opens a documented pull request. ## Quick Start Ask the AI to implement a feature or fix a bug, and it will follow the SDLC workflow from branch creation through pull request delivery.

Frequently Asked Questions about sdlc

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

FAQPage Schema
How do I enforce a consistent workflow for AI coding tasks?▼

Use a step-by-step SDLC workflow that gauges task size first, then applies branch creation, requirements analysis, planning, implementation, testing, and PR creation. Smaller tasks skip heavyweight steps while large changes get full rigor.

How to create a pull request with the GitHub CLI?▼

Create a feature branch with git checkout -b, commit changes atomically, then use the gh CLI to push and open the PR. The workflow assumes gh is installed and authenticated, and stops with instructions if it is missing or unauthenticated.

Does this workflow support GitHub issues as input?▼

Yes. It fetches issue details with gh issue view, branches as fix/issue-123-description, labels the issue in-progress, and posts the plan as a comment before implementing.

Can the AI merge pull requests automatically?▼

No. The workflow explicitly forbids merging PRs. Every pull request is delivered ready for human review and merge, keeping a human gate on all code entering the main branch.

What happens when tests fail during the workflow?▼

Failing tests must be fixed and rerun until they pass. Skipping tests with test.skip or it.skip is forbidden; tests must be fixed, replaced, refactored, or removed, and missing infrastructure must be set up.

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