Orchestrate end-to-end software feature workflows from brainstorming through QA.
npx skills add https://github.com/Mrlyk/superharness --skill go-mrlyk
Please help me install this Agent Skill. Skill: go Source: https://github.com/Mrlyk/superharness/tree/main/skills/go Command: npx skills add https://github.com/Mrlyk/superharness --skill go-mrlyk
Automates the end-to-end software feature workflow inside AI agents, ensuring requirements clarification, planning, implementation, review, and QA are followed mechanically.
The flow guides teams to avoid skipped steps and drift, providing a repeatable process that reduces risk and accelerates delivery.
Provide a complete end-to-end development plan for a new feature given a brief requirement.
High-intent search queries and answers about installing and using this skill.
End-to-end software feature workflow automation orchestrates brainstorming, planning, TDD implementation, dual reviews, and QA within a single session. It creates task artifacts, worktrees, and trace logs to enforce disciplined phases and ensure reproducibility.
Spec compliance and code quality checks are enforced through dual reviews and validation phases. The workflow mechanically applies these quality gates alongside requirement clarification and TDD implementation to prevent skipped steps and reduce delivery risk.
Test-driven development and worktrees are fully supported for feature development within a single session. The workflow decomposes clarified requirements into tasks, implements them using TDD, and creates worktrees to ensure structured management and reproducibility.
AI-driven software engineering workflow explicitly handles requirement clarification and task decomposition. It automates these initial phases before guiding TDD implementation and validation, ensuring teams follow a repeatable process that avoids drift.
Trace logging and contract artifacts are needed to ensure reproducibility and quality in AI-assisted feature development. They provide structured task management and enforce spec compliance throughout the automated brainstorming, implementation, and review phases.
Automating the software development workflow inside AI agents is limited to feature development tasks requiring requirement clarification, TDD implementation, and validation. It enforces disciplined phases mechanically, which may not suit workflows needing flexible or non-linear process steps.
nprbstInterpret Speck artifacts to answer questions about specs, plans, and tasks.
oxieArchive feature artifacts, update roadmap to Shipped, and clean up branches.
pavel-molyanovGuide TDD-driven code writing through preparation, implementation, and post-work phases.
WirasmOrchestrate the five-step PRP workflow from branch creation to pull request.
